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Monarch Business School University for Graduate Studies in Management CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power: An Empirical Comparative Study on the Toronto Stock Exchange (TSX/S&P) and the New York Stock Exchange (NYSE) Indexed Companies
PROGRAM: THESIS SUBMISSION DATE: CANDIDATE: THESIS SUPERVISOR: THESIS COMMITTEE CHAIR: SECOND READER: THIRD READER:
D.Phil. in Business Research 25-April-2013 Mr. Yusuf Mohammed Nulla, M.Sc., M.B.A. Dr. David Bevan, Ph.D. Dr. Jeffrey Henderson, D.Phil. Dr. Donald York, D.Phil. Dr. Gary Keller, Ph.D.
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ACKNOWLEDGEMENTS
I am very grateful for the wise counsel of my supervisor, Dr. David Bevan. Our continuing electronic exchanges were crucial in shaping this research and kept me focused on relevant subject matters. Moreover, his impressive patience approach in this thesis development process had helped me at times when I was frustrated with the daunting tasks of data mining, recording, and automation. In addition, I am also grateful to Dr. Jeffrey Henderson and Dr. Ali Mabrouk for their invaluable assistantships towards the development of my research proposal.
From its inception, this research drew upon the kind provision of data from the Canadian Securities Administrators (CSA) and United States Securities and Exchange Commission. Also, thanks go to senior personnel of the investor relations department of companies whom I have approached for additional information and clarifications. Finally, my heartfelt thanks (as ever indebted) to my late mother, Shireen Banu Nulla, and my father, Mohammed Yusuf Nulla, who have given me unswerving support towards a quest for education particularly, in undertaking this challenging and difficult topic of executive compensation.
1 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
PURPOSES AND ATTESTATION This document is prepared as a Dissertation submission to UGSM-Monarch Business School Switzerland and Universidad Azteca in fulfillment of the degree of: Doctor of Philosophy in Business Research The author hereby attests that the work herein provided in fulfillment of the above degree requirements is wholly of his own effort and hand. Further, the author attests that this document constitutes the entire submission of the dissertation component.
Dissertation Committee Members: Thesis Supervisor
Dr. David Bevan, Ph.D. Professor of Management
Committee Chair:
Dr. Jeffrey Shawn Henderson, D.Phil. Dean of Studies Chair of the Academic Council
Secondary Reader
Dr. Donald York, D.Phil. Professor of Management
Third Reader
Dr. Gary Keller, Ph.D. Professor of Management
____________________________________________ Mr. Yusuf Mohammed Nulla, MSc, MBA
______________ Date
© 2013 Yusuf Mohammed Nulla, All Rights Reserved to Author 2 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
THESIS ABSTRACT This study investigated the relationship between CEO cash compensation, firm size, firm performance, and CEO power, on the Toronto Stock Exchange (TSX/S&P) and New York Stock Exchange (NYSE) indexes companies from 2005 to 2010. The quantitative research method was selected for this research study. The two hundred and forty companies were selected from a stratified sampling method. Thirty-six statistical models were developed for this research study. The research question for this research study was: among TSX/S&P and NYSE indexes companies, is there a relationship between CEO cash compensation, firm size, firm performance, and CEO power. The results found that among TSX/S&P and NYSE indexes companies, there was a relationship between CEO cash compensation, firm performance, firm size, and CEO power, except for the relationships between, CEO bonus and firm size in NYSE medium sized companies, CEO bonus and firm performance in NYSE large sized companies, and CEO Bonus and CEO power in NYSE medium sized companies. The correlations between sub variables of CEO cash compensation, firm size, and firm performance were found to be ranged from weak negative to good positive ratios, among TSX/S&P and NYSE indexes companies. The correlations between sub variables of CEO cash compensation and CEO power were found to range from moderate negative to good positive ratios, among TSX/S&P and NYSE indexes companies. 3 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
TABLE OF CONTENTS ACKNOWLEDGEMENT---------------------------------------------------------
1
PURPOSES AND ATTESTATION--------------------------------------------
2
THESIS ABSTRACT--------------------------------------------------------------
3
CHAPTER ONE: INTRODUCTION-------------------------------------------1.1 CEO Compensation History-------------------------------------------1.1.1 CEO vs. Average Worker Pay---------------------------------1.1.2 CEO Compensation and Social Issue-----------------------1.2 Description of the Research-------------------------------------------1.3 CEO Compensation Problems/Issues-------------------------------1.4 Purpose of Research----------------------------------------------------1.5 Methodology and Methods----------------------------------------------1.6 Research Questions------------------------------------------------------1.7 Hypotheses-----------------------------------------------------------------1.8 Significance of CEO Compensation Study-------------------------1.9 Nature of Study------------------------------------------------------------ 1.10 Limitations and Delimitations-------------------------------------------1.11 Assumptions----------------------------------------------------------------1.12 Summary of the Chapter-------------------------------------------------
10 11 14 20 21 22 25 25 29 30 34 35 36 37 37
CHAPTER TWO: LITERATURE REVIEW----------------------------------2.1 Purpose of Research-----------------------------------------------------2.2 CEO Compensation Theories------------------------------------------2.2.1 CEO Compensation and Agency Problems-----------------2.2.2 CEO Compensation and Agency Contracting------------- -2.2.3 CEO Compensation and Agency Monitoring--------------- -2.2.4 CEO Compensation and Agency Theory and Risk------- -2.2.5 CEO Compensation and Agency Theory and Equity Ownership--------------------------------------------------2.2.6 CEO Compensation and Productivity Theory---------------2.2.7 CEO Compensation and Tournament Theory--------------2.2.8 CEO Compensation and Agency Theory and CEO Power----------------------------------------------------------2.2.9 CEO Compensation and Stewardship Theory and CEO Power-----------------------------------------------------------
39 40 40 40 43 45 46 48 49 50 52 60 4
Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
2.3
2.4 2.5
CEO Compensation and Firm Performance----------------------- -2.3.1 CEO Compensation and Pay Structure----------------------2.3.2 CEO Compensation and Firm Performance Linkage-----2.3.3 CEO Compensation and Return on Assets (ROA)--------2.3.4 CEO Compensation and Return on Equity (ROE)---------2.3.5 CEO Compensation, Stock Ownership, and Stock Price-CEO Compensation and Firm Size------------------------------------2.4.1 CEO Compensation and Firm Size Linkage---------------- --CEO Compensation and CEO Power---------------------------------2.5.1 CEO Compensation and CEO Stock Ownership---------- --2.5.2 CEO Compensation and CEO Tenure----------------------- --2.5.3 CEO Compensation and CEO Age--------------------------- --2.5.4 CEO Compensation and CEO Turnover----------------------2.5.5 CEO Compensation and 5% Management Ownership----2.5.6 CEO Compensation and 5% Individual/Institutional Ownership-------------------------------------------------------------
63 63 65 75 76 79 81 81 84 84 86 88 89 90 92
CHAPTER 3: METHODOLOGY AND METHODS-------------------------3.1 General description---------------------------------------------------------3.2 Method Selected------------------------------------------------------------3.3 Appropriateness-------------------------------------------------------------3.4 Research Design------------------------------------------------------------3.5 Validity and Reliability------------------------------------------------------3.6 Sampling Method------------------------------------------------------------3.7 Data Collection---------------------------------------------------------------3.8 Data Analysis-----------------------------------------------------------------3.9 Summary----------------------------------------------------------------------3.9.1 Description of Data Finding Presentation----------------------
94 95 95 98 100 103 106 107 111 115 117
CHAPTER 4: DATA PRESENTATION----------------------------------------4.1 Purpose of Dissertation---------------------------------------------------4.2 Research Method-----------------------------------------------------------4.3 Data Collection--------------------------------------------------------------4.4 Data Distillation--------------------------------------------------------------4.5 Data Findings----------------------------------------------------------------4.5.1 Null Hypothesis Testing------------------------------------------4.5.1.1 Operational Hypothesis Statement 1--------------4.5.1.2 CEO Cash Compensation vs. Firm Size (TSX/S&P & NYSE Small, Medium, and Large Populations)--------------------------------4.5.2 Operational Hypothesis Statement 2----------------------------
119 120 120 121 123 125 125 125 127 132 5
Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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4.5.2.1 CEO Cash Compensation vs. Firm Size (TSX/S&P & NYSE Small, Medium, and Large Populations)----------------------------------4.5.3 Operational Hypothesis Statement 3------------------------4.5.3.1 CEO Cash Compensation vs. CEO Power (TSX/S&P & NYSE Small, Medium, and Large Populations)------------------------------------
134 146 148
CHAPTER 5: SYNTHESIS-----------------------------------------------------5.0 Chapter Introduction-----------------------------------------------------5.1 Synthesis: CEO Cash Compensation and Firm Size------------5.2 Synthesis: CEO Cash Compensation and Firm Performance-5.3 Synthesis: CEO Cash Compensation and CEO Power---------5.4 CEO Cash Compensation Models------------------------------------5.5 Chapter Conclusion-------------------------------------------------------
161 162 163 167 180 195 199
CHAPTER 6: CONCLUSIONS AND FUTURE STUDY------------------6.1 Conclusions and Findings of the research study------------------6.1.1 Conclusions - CEO Cash Compensation vs. Firm Size--6.1.2 Conclusions - CEO Cash Compensation vs. Firm Performance-------------------------------------------------------- 6.1.3 Conclusions - CEO cash Compensation vs. CEO Power 6.2 Future Research-----------------------------------------------------------6.3 Final Summary--------------------------------------------------------------
204 205 211
BIBLIOGRAPHY--------------------------------------------------------------------
225
BIBLIOGRAPHIC REVIEW------------------------------------------------------
250
APPENDICES----------------------------------------------------------------------Appendix A - Definitions----------------------------------------------------------Appendix B - Company Names-------------------------------------------------Appendix C - Survey Questions------------------------------------------------Appendix D - Statistical Results------------------------------------------------Section 1.1 TSX/S&P Small Size Company - Salary vs. Total Sales and Total Employees--------------------Section 1.2 TSX/S&P Small Size Company - Bonus vs. Total Sales and Total Employees--------------------Section 1.3 NYSE Small Size Company - Salary vs. Total Sales and Total Employees---------------------
253 254 263 267 275
212 216 220 224
275 285 296 6
Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Section 1.4 NYSE Small Size Company - Bonus vs. Total Sales and Total Employees--------------------Section 1.5 TSX/S&P Medium Size Company - Salary vs. Total Sales and Total Employees--------------------Section 1.6 TSX/S&P Medium Size Company - Bonus vs. Total Sales and Total Employees--------------------Section 1.7 NYSE Medium Size Company - Salary vs. Total Sales and Total Employees--------------------Section 1.8 NYSE Medium Size Company - Bonus vs. Total Sales and Total Employees--------------------Section 1.9 TSX/S&P Large Size Company - Salary vs. Total Sales and Total Employees--------------------Section 1.10 TSX/S&P Large Size Company - Bonus vs. Total Sales and Total Employees--------------------Section 1.11 NYSE Large Size Company - Salary vs. Total Sales and Total Employees--------------------Section 1.12 NYSE Large Size Company - Bonus vs. Total Sales and Total Employees--------------------Section 2.1 TSX/S&P Small Size Company - Salary vs. Performance----------------------------------------------Section 2.2 TSX/S&P Small Size Company - Bonus vs. Performance----------------------------------------------Section 2.3 NYSE Small Size Company - Salary vs. Performance----------------------------------------------Section 2.4 NYSE Small Size Company - Bonus vs. Performance----------------------------------------------Section 2.5 TSX/S&P Medium Size Company - Salary vs. Performance----------------------------------------------Section 2.6 TSX/S&P Medium Size Company - Bonus vs. Performance----------------------------------------------Section 2.7 NYSE Medium Size Company - Salary vs. Performance----------------------------------------------Section 2.8 NYSE Medium Size Company - Bonus vs. Performance ---------------------------------------------Section 2.9 TSX/S&P Large Size Company - Salary vs. Performance----------------------------------------------Section 2.10 TSX/S&P Large Size Company - Bonus vs. Performance----------------------------------------------Section 2.11 NYSE Large Size Company - Salary vs. Performance----------------------------------------------
306 315 323 333 341 350 358 366 374 382 394 409 395 423 449 462 474 487 499 503 7
Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Section 2.12 NYSE Large Size Company - Bonus vs. Performance---------------------------------------------Section 3.1 TSX/S&P Small Size Company - Salary vs. CEO Power-----------------------------------------------Section 3.2 TSX/S&P Small Size Company - Bonus vs. CEO Power-----------------------------------------------Section 3.3 NYSE Small Size Company - Salary vs. CEO Power-----------------------------------------------Section 3.4 NYSE Small Size Company - Bonus vs. CEO Power-----------------------------------------------Section 3.5 TSX/S&P Medium Size Company - Salary vs. CEO Power-----------------------------------------------Section 3.6 TSX/S&P Medium Size Company - Bonus vs. CEO Power-----------------------------------------------Section 3.7 NYSE Medium Size Company - Salary vs. CEO Power-----------------------------------------------Section 3.8 NYSE Medium Size Company - Bonus vs. CEO Power-----------------------------------------------Section 3.9 TSX/S&P Large Size Company - Salary vs. CEO Power-----------------------------------------------Section 3.10 TSX/S&P Large Size Company - Bonus vs. CEO Power-----------------------------------------------Section 3.11 NYSE Large Size Company - Salary vs. CEO Power-----------------------------------------------Section 3.12 NYSE Large Size Company – Bonus vs. CEO Power------------------------------------------------
525 538 550 562 573 585 597 609 621 633 645 657 669
8 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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LIST OF TABLES Table 4.5.1.2A Table 4.5.1.2B Table 4.5.2.1A Table 4.5.2.1B Table 4.5.3.1A Table 4.5.3.1B
ANOVA (TSX/S&P - CEO Cash Compensation vs. Firm Size)-----------------------------------------------------ANOVA (NYSE – CEO Cash Compensation vs. Firm Size)-----------------------------------------------------ANOVA (TSX/S&P - CEO Cash Compensation vs. Firm Performance)------------------------------------------ANOVA (NYSE – CEO Cash Compensation vs. Firm Performance)------------------------------------------ANOVA (TSX/S&P - CEO Cash Compensation vs. CEO Power)--------------------------------------------------ANOVA (NYSE – CEO Cash Compensation vs. CEO Power)---------------------------------------------------
127 128 135 135 149 149
LIST OF FIGURES Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6
CEO to Worker Compensation Ratio------------------CEO Compensation and CEO-to-Worker Ratio-----CEO/Worker Payout Ratio--------------------------------Quantitative Research Design---------------------------TSX/S&P & NYSE Salary Models-----------------------TSX/S&P & NYSE Bonus Models------------------------
16 17 19 102 195 196
9 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
CHAPTER ONE INTRODUCTION
10 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
CHAPTER ONE - INTRODUCTION 1.1 CEO COMPENSATION HISTORY The compensation of CEOs continues to attract the interest of shareholders, academics, media, and the general public. It is believed that the recent growth in CEO pay, against the backdrop of corporate scandals and governance failures that plagued corporations around the world, has put executive compensation at the center of the debate on corporate governance. Historically, according to Saks and Frydman (2010), the compensation trend is remarkably flat from the late 1940s to the 1970s, indicating a weak relationship between pay and aggregate firm growth. The level of pay and the use of stock options are lower from the 1950s to the 1970s than they are in more recent years, despite corporate governance does not appear to have been stronger in the past (Saks and Frydman, 2010). That is, the composition of executive compensation also changed considerably since the 1950s, as both stock options and other forms of incentive pay became larger shares of total compensation over time. In addition, they find that the growth in executive pay cannot be explained by changes in board characteristics, the rise of shareholders who own large blocks of stock, or the decline in family owned firms. In contrast, the correlation is much stronger from 1970 to 2000. That is, after a sharp decline during WWII, the level of pay increased slowly from the mid-1940s to the mid-1970s and then rose at an increasing rate from the 1970s to the 11 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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present. Murphy (1999) finds that the compensation paid to CEOs of large publicly traded corporations rose dramatically during the 1980s and 1990s, which prompted an investigation of the underlying factors that determine managerial pay. Evans and Hefner (2008) states that, from a compensation growth perspective, the nineties were a great time to be a top executive in a large U.S. company (Evans and Hefner, 2008). The median total compensation of CEOs nearly tripled from $2.3 million in 1992 to over $6.5 million in 2000 in the S&P 500 Industrials. The primary driver of this remuneration spike was the dramatic growth in stock options that grew from 27 percent to 51 percent of total compensation. Bebchuk and Fried (2003, 2004) believed that the rise in CEO pay and the expanded use of stock options have been linked to managers’ ability to extract rent (compensation) from the firm. They stated that:
“Firstly, seeking to make pay more sensitive to performance, regulators and shareholders encouraged the use of equity-based compensation. Taking advantage of this enthusiasm, executives used their influence to obtain substantial option pay without giving up corresponding amounts of their cash compensation; furthermore, the options they received did not link pay tightly to the managers’ own performance but rather enabled managers to reap windfalls from that part of the stock price increase due solely to market and sector trends beyond their control; as a result, managers were able to capture much larger gains than more cost-effective and efficient plans would have provided. 12 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Secondly, because executive compensation has historically been correlated with market capitalization, the rising stock markets of the 1990s, which carried along with them even many poorly performing companies, provided a convenient justification at most firms for substantial pay increases. Thirdly, market booms weaken outrage constraints; exuberant shareholders are less likely to scrutinize and resent generous pay arrangements, in the same way that the recent market declines has made shareholders more prone to do so”.
Bebchuk and Grinstein (2005) reports that, between 1993-2003, the average total CEO compensation for S&P500 firms increased by 166 percent, of which only 66 percent is explained by an increase in firm size measured by sales and performance measured by return on assets with the rest remaining unexplained.1 According to Murphy (2002), the executive pay increases resulted not from changes in managerial power but rather from other factors. Perhaps, other rationales for CEO pay increase is linked to a risk-based CEO compensation structure, the information technology revolution and skilled-biased technical change, improvements in board diligence, enhanced disclosure of financial
1 According to Forbes (“Big paychecks”, March 5, 2007), the collective total CEO pay for the largest 500 firms in the US increased by 38 percent during 2005-2006. During the same period, the S&P500 index rose by 15.79 percent. Numerous articles in the media report high-profile cases of ‘excessive’ CEO pay despite mediocre firm performance such as: The Economist (November 24, 2005), “Too many turkeys”; The Economist (January 18, 2007), “Power pay”; Fortune (June 30, 2006), “The real CEO pay problem”; The New York Times (January 4, 2007), “An ousted chief’s going-away pay is seen by many as typically excessive”.
13 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
information to compensate executives for the disutility of stronger monitoring, and changes in social norms, perhaps the increase in CEO pay in recent decades. According to Harris (2008), some CEOs profited greatly even as their firms and stakeholders suffered financial downturns. In some instances, the board of directors adjusted performance targets to make meeting benchmark standards much easier to achieve. There are a number of examples of companies in 2008 that did not tie its CEO pay levels close to adding to shareholder value. For example, Warner Music Group paid its CEO Edgar Bronfman a $3 million bonus for an operating year in which the company experienced a $56 million loss and its share price fell by 25%. The rationale for the bonus payout was management outperformed the industry and the firm wanted to reward strong operating performance in a historically challenging industry environment. Similarly, Varian Semiconductor CEO Gary Dickerson received over $1 million in incentive pay despite a 53% stock price decline and a 31% drop in net income, rationales provided were management team exceeded target market share and new business expansion. 1.1.1 CEO vs. Average Worker Pay History In the past several decades, the difference between the compensation of corporate chief executives and the pay earned by the average employee has increased dramatically. In 1960, the average chief executive earned 40 times as much as the average worker. By 1990, the average CEO earned 107 times as much. In the following 14 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
decade, this ratio rose to 525:1 before settling back to 301:1 in 2003.2 In a paper published by the Economic Policy Institute, a think-tank, calculates that chief executives at the America's 350 biggest companies are paid 2313 times as much as the average private-sector worker in 2011 (figure 4 below). This ratio, which includes the value of share options, has begun to rise again after falling during the recession, considering wages in the United States have been flat for years while CEO pay has risen substantially. Using a measure of CEO compensation that includes the value of stock options granted to an executive, the CEO-to-worker compensation ratio was 18.3-to-1 in 1965, peaked at 411.3-to-1 in 2000, and reached to 209.4-to-1 in 2011 (figure 4 and 5 below). Using an alternative measure of CEO compensation that includes the value of stock options exercised in a given year, CEOs earned 20.1 times more than average workers in 1965, 383.4 times more in 2000, and 231.0 times more in 2011 (figure 4 and 5 below). The fall in the stock market after the year 2000 reduced CEO stock options and caused CEO compensation to tumble until 2002 and 2003. The CEO compensation recovered to a level of 351.7 times worker pay by 2007. The CEO-to-worker compensation ratio based on options-granted, however, increased only to 244.1-to-1 in 2007. The financial crisis in 2008 and accompanying stock market decline reduced CEO compensation after 2007–2008, and the CEO-to-worker compensation ratio fell in tandem. By 2011, the stock market has recovered from the losses incurred during the 2
Thompson, Derek (2013), ‘What’s Behind the Huge (and growing) CEO –Worker Pay Gap?, The Atlantic, April 30. 3 Mishel, Lawrence and Sabadish, Natalie (2012), ‘CEO pay and the top 1%’, Issue Brief, Economic th Policy Institute, May 2, 12 Edition, pp.1-7.
15 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
financial crisis. The CEO compensation grew 78.7 percent between 1965 and 1978, three times the growth of the compensation of private-sector workers. The CEO compensation grew strongly over the 1980s but exploded in the 1990s and peaked in 2000 at a growth of 1,390 percent, from 1978. This growth in CEO compensation far exceeded the stock market value over the 1980s and 1990s. Overall, CEOs have received far better compensation than typical worker, stock market, or the U.S. economy over the last several decades.
FIGURE 1 CEO-to-Worker Compensation Ratio With Options Granted and Options Realized,1965–2011!
Source: (Mishel, Lawrence and Sabadish, Natalie, ‘CEO pay and the top 1%’, 2012, Issue Brief, th Economic Policy Institute, May 2, 12 Edition)
16 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
FIGURE 2 CEO Compensation and CEO-to-Worker Compensation Ratio 1965–2011 (2011 dollars) CEO annual compensation (thousands) Options realized
Options granted
Worker annual compensation (thousands) Privatesector
Firms’ industry
Stock market indices (inflationadjusted) S&P 500
Dow Jones
CEO-to-worker compensation ratio Options realized
Options granted
1965 $791
$750
$38
n/a
511
5,278
20.1
18.3
1973 1,033
980
45.8
n/a
451
3,881
22.1
20.1
1978 1,413
1,341
47.6
n/a
282
2,411
29.0
26.5
1989 2,631
2,496
44.0
n/a
525
4,081
58.5
53.3
1995 5,570
6,177
43.6
49.8
737
6,120
122.6
136.8
2000 19,482
19,977
45.9
52.0
1,730
13,006
383.4
411.3
2007 17,919
12,484
48.2
52.2
1,487
13,268
351.7
244.1
2008 17,491
11,648
48.4
53.0
1,183
10,902
314.9
225.7
2009 10,036
9,639
50.5
55.4
923
8,648
193.1
181.5
2010 12,042
11,003
50.9
56.0
1,092
10,215
228.0
205.9
2011 12,141
11,082
50.3
55.4
1,268
11,958
231.0
209.4
Percent change
Change in ratio
1978– 759.3% 2011
726.7%
5.7%
n/a
349.1%
395.9%
202.0
182.9
1965– 78.7 1978
78.7
23.7
n/a
-44.7
-54.3
8.9
8.1
1978– 1,278.8 2000
1,390.3
-3.6
n/a
513.0
439.3
354.4
384.9
2000– -37.7 2011
-44.5
9.7
6.6%
-26.7
-8.1
-152.4
-201.9
Source: Accessed: June 18, 2012, Economic Policy Institute: http://stateofworkingamerica.org/chart/swa-wages-table-4-43-ceo-compensation-ceo/
17 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Similarly, in Figure 3 below, five companies with the highest CEO/worker pay ratio compared with the S&P average and the 1965 average among the 350 largest companies, the average multiple of CEO compensation to that of rank-and-file workers is 204 times. The top five CEO compensation has far exceeded both the average worker and average S&P 500 companies compensation, ranged from 1175 to 1800 times. Bebchuk and Grinstein (2005) explained this increased CEO pay trend to changes in firm size, performance, and industry classification. From 1978–2011, CEO compensation grew more than 725 percent4, substantially more than the stock market and remarkably more than worker compensation, at a meager 5.7 percent. According to Bebchuk and Grinstein (2005), among S&P 500 firms, average CEO compensation climbed from $3.7 million in 1993 to $9.1 million in 2003 (an increase of 146%), and average compensation to top-five executives increased from $9.5 million in 1993 to $21.4 million in 2003 (an increase of 125%). “Between 1993 and 2003, firm size increased considerably. The average size of the S&P 500 firms, as measured by sales, increased by 40% (inflation-adjusted) from 1993-1995 to 2001-2003. During the same period, the average size of the Mid-Cap 400 firms increased by 30% and the average size of the Small-Cap 600 firms increased by 51%. Furthermore, during the considered period, the incidence of new economy firms, where compensation has been somewhat
4
Mishel, Lawrence and Sabadish, Natalie (2012), ‘CEO pay and the top 1%’, Issue Brief, Economic Policy Institute, May 2, 12th Edition, pp.1-7.
18 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
higher, has increased. These changes in size and industry classification might account for some of the growth in compensation figures.
FIGURE 3 CEO/Worker Payout Ratio
Source: Derek Thompson, ‘What’s Behind the Huge (and Growing) CEO-Worker Pay Gap?, The Atlantic, 2013, April 30
19 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Himmelberg and Hubbard (2000) and Hubbard (2005) suggest that, during a period of market booms, the demand for executives goes up and firms need to pay more in order to retain and hire executives. In addition, the hiring of CEOs from outside the firm has increased which strengthened executive bargaining positions. Spatt (2004) suggests that the bull market increased the wealth of executives, which in turn increased their reservation wage by increasing the monetary amount needed to induce executives to work. Bebchuk and Fried (2004) argues that outsiders’ enthusiasm for incentive-based compensation provided executives and directors with opportunities to raise pay levels substantially in ways that would appear acceptable to outsiders. Murphy and Zabojnik (2004) links the increase in CEO pay to the increase in CEO turnover. 1.1.2 CEO Compensation and Social Issue Institutional shareholders, politicians, and the public have blamed boards that executives are paid too much, and that the current incentive-pay schemes are flawed because the connection between executive pay and company performance is mixed at best, and at worst, has led to a series of dysfunctional behaviors. They believed that executive compensation should be based on pay for performance against sectorspecific environmental, social and governance criteria, as well as financial performance indicators. The solutions offered for the problems of excessive levels of executive pay and the need to strengthen the link between pay and performance often solution to: strengthen the independence of directors and compensation committees; increase the 20 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
shareholders’ rights to elect directors and to express their views on compensation plans, to discourage manipulation of CEO compensation and align incentives more closely with the aims of the owners. It is believed that these problems can be solved with an effective compensation structure or improved techniques to link CEO pay to stock performance. A recent McKinsey survey commissioned by the Canadian Coalition for Good Governance found that an overwhelming majority of directors and investors wished to see factors such as sustainable development and customer satisfaction considered in setting compensation, yet only a minority of Canadian companies appear to link these factors with executive compensation.
1.2 DESCRIPTION OF THE RESEARCH Over the past decade in Canada and the United States, institutional shareholders, investor groups, and the public have raised concern over the quantum of remuneration packages offered to CEOs. They are highly alarmed and surprised to learn of increased in CEO pay during period of the global credit crunch from 2007 to 2009. They believed that CEOs should strictly be paid on the basis of accounting performance and the financial position of a company. In addition, from a research point of view, most of the previous studies have used a single independent variable such as firm size, firm performance, or CEO power to understand CEO compensation as such, failed to understand CEO compensation system on a comprehensive basis. That is, to understand CEO compensation system requires combinations of multi-variables 21 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
comprised of dependent and independent variables as such, lacked focus, comprehensiveness, and discipline, to understand true determinants of CEO compensation. Overall, all of these shortcomings suggest the need to conduct new research on CEO compensation system as such, this research study will try to understand the relationship between CEO cash compensation, firm size, firm performance, and CEO power, among TSX/S&P and NYSE indexes companies from 2005 to 2010. In addition, this research study results will be used to perform comparative analysis between TSX/S&P and NYSE indexes companies, so as to better understand their respective CEO cash compensation systems.
1.3 CEO COMPENSATION PROBLEMS/ISSUES The CEO compensation system has been greatly misunderstood by the public for some time but it has been emerged as a concern during the period of the global credit crunch from 2007 to 2009. The general social ethical belief is that CEOs should be rewarded based on accounting performance and should be penalized if companies perform below market expectations. This belief resulted in numerous single studies conducted in the United States and United Kingdom, yet these studies have failed to arrive at robust conclusions on the relationship between CEO pay and performance. Gomez-Mejia and Barkema (1998) admitted that after six decades of research, the failure to identify a robust relationship between executive compensation and firm performance has led scholars into a blind alley. A factor analysis conducted by Tosi, Werner, Katz and 22 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Gomez-Mejia (1998) finds that less than 5 percent of CEO pay is explained by performance factors. Dyl (1998) stated that there is a downside hedge of a CEO’s pay in management controlled firms, given that it is more strongly related to firm size, not firm performance. Williams (1985) believed that executives themselves set their pay using outside consultants to legitimize compensation package therefore transparency is minimized within decision making system. Jensen and Murphy (1990) and Hubbard and Palia (1995) favored performance to be measured by shareholder value. On the other hand, Nyberg, Fulmer, Gerhart and Carpenter (2010) measured firm performance using net income, return on equity, and return on assets. The great scholars in the field of executive compensation such as, Gomez-Mejia, Eugene F. Fama, Michael Jensen, and Kevin Murphy have expressed concerns: why are robust conclusions not achieved; why these studies have arrived at divergent or inconsistent results; and why it has failed to establish defining factors that influenced CEO compensation system. Tosi et al. (2000) have blamed these concerns to different methods of collection, different statistical techniques, different samples, different moderator variables, and differences in how constructs of interest have been used in various studies. As such, these reasons have hampered to reach definite and consistent conclusions among previous studies. In addition, CEO cash compensation has rarely been studied as a separate study despite it is believed to be a strong proxy towards determining CEO total compensation. That is, CEO cash compensation which includes salary and bonus is sufficient to represent CEO total compensation which comprised of salary, bonus, stock options, pensions, 23 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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and other long-term benefits. Agarwal (1981), Finkelstein & Boyd (1998), and Finkelstein and Hambrick (1989,1996) concluded that simple measures of cash compensation are an excellent proxy for CEO total pay. Similarly, Mehran (1992) reported that CEOs took 67% of total pay in the form of salary and a bonus and 22% in the form of equity based incentives.
The literature indicated that most of previous studies have focused on the industry segment for sampling, thus biasing the results. In addition, sample sizes have ranged from fifty to eight hundred therefore the results are inconsistent. From a firm size perspective, previous studies have used either total revenues, total assets, or total number of employees as a proxy for firm size as such the results are also inconsistent. From a firm performance perspective, previous studies have used either return on equity, return on assets, earnings per share, cash flow per share, or market value per share as a proxy for firm performance as such the results are also inconsistent. From a CEO power perspective, previous studies have used either CEO age, CEO tenure, or CEO duality role as a proxy for CEO power as such the results are also inconsistent. From a timing perspective, previous studies have ranged from one to ten year period as such has affected the quality and consistency of statistical results. Overall, previous studies have failed to understand the CEO compensation system either due to: the few variables used in their studies; the focus on a distinct population segment; or the use of different statistical methodologies. 24 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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1.4 PURPOSE OF THE RESEARCH The purpose of this research is to investigate in clear terms the extent and nature of the relationship between CEO cash compensation, firm size, firm performance, and CEO power, among TSX/S&P and NYSE indexes companies from 2005 to 2010. To educate shareholders, investors, and the public on determinants of CEO cash compensation. That is, compensation factors that involved in rewarding CEOs with salaries and bonuses. In addition, contribute in the field of executive compensation literature with recent findings.
1.5 METHODOLOGY AND METHODS This research requires a process of deductive reasoning by use of measurement tools to collect, count, and classify data. It demands a high level of objectivity and impartiality in processing and assessments, to achieve clear conclusions. In addition, it requires the use of statistical calculations to understand the nature and extent of the relationship between CEO cash compensation, firm size, firm performance, and CEO power. As such, quantitative research method will be adopted for this research study. According to Cormack (1991), quantitative research methodology tests deductive theory of existing knowledge through the development of hypothesized relationships and proposed outcomes. The process of measurement is central to quantitative research because it provides a fundamental connection between empirical observation and mathematical 25 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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expression of quantitative relationships. In addition, Creswell (2009) stated that if problem calls for identification of factors that influence an outcome, the utility of an intervention, or understanding clear outcomes, then a quantitative approach is most suitable.
Within the system of quantitative research framework, this research will select a longitudinal study method to collect six years of data from 2005 to 2010. It will select the survey method for longitudinal studies. It will select stratified sampling method to achieve equal stratum and avoid selection bias towards determining sample sizes of small, medium, and large for TSX/S&P and NYSE respective populations. Each population will be based on one hundred and twenty companies. Each sub population or firm size will consist of forty companies. The firm size will be determined on total revenues. The small size companies will be selected based on total revenues of up to five hundred million dollars. The medium size companies will be selected based on total revenues of over five hundred million to two billion dollars. The large size companies will be selected based on total revenues of over two billion dollars. These specific ranges have been created to ensure that a maximum number of companies from a diverse industry background will be available for a stratified sampling. The overall sample size of fourteen hundred and forty observations (six years times two hundred and forty companies) will be used for statistical testing, which are believed to provide strong power to produce clear and credible results. The data will be collected from financial 26 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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years ending on or after Jan. 1, 2005 to Dec. 31, 2010. To avoid a potential loss of data during the study period, companies will be sampled backward from 2010 to 2005 onwards. This approach will be taken to obtain consistent data from each company. In addition, such a sampling technique will assist a total number of firms that may fall off due to separation, merger, or acquisition. The structured questionnaire approach will be adopted to collect data on CEO cash compensation, firm size, financial performance, and CEO power. The survey will consist of fourteen questions.
Descriptive and inferential statistics approaches will be used to transform surveyed data into statistical results. The data analysis will be performed by calculating response rate, checking range and validity of data, producing summary tables, illustrating with graphs and charts, and drawing summary statistics. The statistical software package SPSS will be used for this study. The linear regression statistical method will be used to study the relationship between CEO cash compensation, firm size, firm performance, and CEO power. It consists of calculating mean, standard deviation, confidence interval (significance), regression (R2), analysis of variance (ANOVA), coefficients, coefficient correlation, collinearity diagnostics, residual statistics, histogram, plot of regression standardized statistics, and partial regression residual plots.
In this research study, CEO cash compensation will be used as dependent variable, firm performance and CEO power will be used as independent variables, and firm size will 27 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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be used as both independent and control variable. The sub dependent variables of CEO cash compensation will be salary and bonus. The sub independent and control variables of firm size will be total revenues and total number of employees. The sub independent variables of firm performance will be return on equity, return on assets, earnings per share, cash flow per share, net profit margin, common stocks outstanding, book value of common stocks outstanding, and market value of common stocks outstanding. The sub independent variables of CEO power will be CEO age, CEO total stock holdings, total value of CEO stocks, CEO tenure, CEO turnover, 5% management ownership, and 5% individual/institutional ownership.
The aim and objective of this research is to show a relationship between CEO cash compensation, firm size, firm performance, and CEO power, among TSX/S&P and NYSE indexes companies. The literature on agency theory will be discussed as a framework to understand theoretical aspects of the CEO compensation system. The null hypothesis will be stated based on the assumption that CEO cash compensation is not related to firm size, firm performance, and CEO power, among TSX/S&P and NYSE indexes companies. Conversely, alternative hypothesis will be stated on the assumption that CEO cash compensation is related to firm size, firm performance, and CEO Power, among TSX/S&P and NYSE indexes companies. Each research question will consist of: research hypothesis, research hypothesis statement, operational hypotheses, and an operational hypothesis statement. The operational hypothesis statement will be based 28 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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on sub variables of CEO cash compensation, firm size, firm performance, and CEO power. Each statistical model will consist of one sub dependent variable of CEO cash compensation with all sub independent variables of firm size, firm performance, or CEO power. For example, CEO salary with total revenues; CEO salary with return on assets, return on equity, earnings per share, cash flow per share, net profit margin, common stocks outstanding, book value per share, and market value per share; or CEO salary with CEO age, CEO total stock holdings, total value of CEO stocks, CEO tenure, CEO turnover, 5% individual/institutional ownership, and 5% management ownership. The total of thirty six statistical models will be developed for this research study. The 95% confidence interval will be assigned for all statistical tests. In the end, regression and correlation results will be analyzed to draw conclusions. The results of each statistical model will be presented separately in Appendix D of this research paper.
1.6 RESEARCH QUESTIONS Research Question 1: Among TSX/S&P and NYSE indexes companies, what relationship is there between CEO cash compensation and firm size?
Research Question 2: Among TSX/S&P and NYSE indexes companies, what relationship is there between CEO cash compensation and firm performance? 29 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Research Question 3: Among TSX/S&P and NYSE indexes companies, what relationship is there between CEO cash compensation and CEO power?
1.7 HYPOTHESES Research Hypothesis 1: Among TSX/S&P and NYSE indexes companies, what relationship is there between CEO cash compensation and firm size.
Research Hypothesis Statement 1: H0 :
Among TSX/S&P and NYSE indexes companies, there is no relationship between CEO cash compensation and firm size.
H1 :
Among TSX/S&P and NYSE indexes companies, there is a relationship between CEO cash compensation and firm size.
Operational Hypotheses 1: A. Among TSX/S&P and NYSE indexes companies, what relationship is there between CEO salary, CEO bonus, return on sales, and total number of employees.
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Operational Hypotheses Statement 1: HA0: Among TSX/S&P and NYSE indexes companies, there is no relationship between CEO salary, CEO bonus, return on sales, and total number of employees. HA1: Among TSX/S&P and NYSE indexes companies, there is a relationship between CEO salary, CEO bonus, return on sales, and total number of employees
Research Hypothesis 2: Among TSX/S&P and NYSE indexes companies, what relationship is there between CEO cash compensation and firm performance.
Research Hypothesis Statement 2: H0 :
Among TSX/S&P and NYSE indexes companies, there is no relationship between CEO cash compensation and firm performance.
H1 :
Among TSX/S&P and NYSE indexes companies, there is a relationship between CEO cash compensation and firm performance.
Operational Hypotheses 2: A. Among TSX/S&P and NYSE indexes companies, what relationship is there between CEO salary, CEO bonus, return on assets, return on equity, earnings per share, cash flow per share, net profit margin, common stocks outstanding, 31 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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book value of common stocks outstanding, and market value of common stocks outstanding.
Operational Hypotheses Statement 2: HA0: Among TSX/S&P and NYSE indexes companies, there is no relationship between CEO salary, CEO bonus, return on assets, return on equity, earnings per share, cash flow per share, net profit margin, common stocks outstanding, book value of common stocks outstanding, and market value of common stocks outstanding. HA1: Among TSX/S&P and NYSE indexes companies, there is a relationship between CEO salary, CEO bonus, return on assets, return on equity, earnings per share, cash flow per share, net profit margin, common stocks outstanding, book value of common stocks outstanding, and market value of common stocks outstanding.
Research Hypothesis 3: Among TSX/S&P and NYSE indexes companies, there is a relationship between CEO cash compensation and CEO power.
Research Hypothesis Statement 3: H0 :
Among TSX/S&P and NYSE indexes companies, there is no relationship between CEO cash compensation and CEO power. 32 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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H1 :
Among TSX/S&P and NYSE indexes companies, there is a relationship between CEO cash compensation and CEO power.
Operational Hypotheses 3: A. Among TSX/S&P and NYSE indexes companies, there is a relationship between CEO salary, CEO bonus, CEO age, CEO total stock holdings, total value of CEO stocks, CEO tenure, CEO turnover, 5% management ownership, and 5% individual/institutional ownership.
Operational Hypotheses Statement 3: HA0: Among TSX/S&P and NYSE indexes companies, there is no relationship between CEO salary, CEO bonus, CEO age, CEO total stock holdings, total value of CEO stocks, CEO tenure, CEO turnover, 5% management ownership, and 5% individual/institutional ownership. HA1: Among TSX/S&P and NYSE indexes companies, there is a relationship between CEO salary, CEO bonus, CEO age, CEO total stock holdings, total value of CEO stocks, CEO tenure, CEO turnover, 5% management ownership, and 5% individual/institutional ownership.
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1.8 SIGNIFICANCE OF CEO COMPENSATION STUDY The CEO cash compensation topic has not been extensively researched nor has been studied on a comparative basis between Canadian and American public companies. This research study will try to educate shareholders, investors, and the public on the determinants of CEO cash compensation. That is, the compensation factors that are involved in rewarding CEOs with salaries and bonuses. It will try to understand the nature and extent of the relationship between CEO cash compensation, firm size, firm performance, and CEO Power, among TSX/S&P and NYSE populations from 2005 to 2010. It will use firm sizes (small, medium, and large) as a control variable to study relationships and correlations between them. It will perform comparative analysis on respective CEO cash compensation systems of TSX/S&P and NYSE populations. It consists of a sample of two hundred and forty companies. It will perform thirty six statistical tests to answer three research questions. Moreover, this research will hope to contribute to the executive compensation literature by developing new theories, and publish articles and book in peer review journals.
1.9 NATURE OF STUDY This research study will be an empirical study and will consist of two hundred and forty companies from TSX/S&P and NYSE populations. Each population will consist of one hundred and twenty companies and each sub population or firm size will consist of forty 34 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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companies. This research will try to understand the nature and extent of influence of firm size, firm performance, and CEO power on CEO cash compensation, among TSX/S&P and NYSE indexes companies. It will use firm size as a control variable to understand relationships and correlations between them. It will consist of three research questions. The first research question is: among TSX/S&P and NYSE indexes companies, is there a relationship between CEO cash compensation and firm size?. The second research question is: among TSX/S&P and NYSE indexes companies, is there a relationship between CEO cash compensation and firm performance?. The third research question is: among TSX/S&P and NYSE indexes companies, is there a relationship between CEO cash compensation and CEO power?. This research will adopt a quantitative research method, longitudinal studies from 2005 to 2010, stratified sampling method to select two hundred and forty companies, survey method to collect historical data, and linear regression method to conduct statistical tests. It will develop thirty-six statistical models to answer three research questions. Each model will be tested based on respective operational hypotheses. The results will be used to accept or reject the null hypotheses of three research questions. In the end, new theories will be developed based on statistical findings. Overall, this research will follow the disciplines of objectivity, clarity, precision, and factual presentation.
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1.10 LIMITATIONS AND DELIMITATIONS 1.10.1 Limitations The long term CEO compensation system which includes stock options, pensions, and other long term benefits will not be investigated. As such, this study will unable to fully explore and generalize the prevalence of pay for performance schemes in its entirety. In addition, since this research will be a macro study on TSX/S&P and NYSE populations, it will unable to study on an industry basis.
1.10.2 Delimitations: This research study primary objective to understand the relationship between CEO cash compensation, firm size, firm performance, and CEO power on firm size basis as such requires to adopt stratified sample method. The websites, Canadianbusiness.com and NYSE.com, will be used to obtain a sample of total of two hundred and forty companies. The data collection period will be from 2005 to 2010. The CEO cash compensation will be determined based on cash and bonus. The firm sizes will be determined based on total revenues. The firm performance will be determined based on return on equity, return on assets, earnings per share, cash flow per share, net profit margin, cash flow per share, common stocks outstanding, book value of common stocks outstanding, and market value of common stocks outstanding. The CEO power will be determined based
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on CEO age, CEO total stock holdings, total value of CEO stocks, CEO tenure, CEO turnover, 5% management ownership, and 5% individual/institutional ownership.
1.11 ASSUMPTIONS The first assumption will be that Canada and the United States currencies are at par from 2005 to 2010. The second assumption will be that inflation is assumed to be a nonfactor in evaluating firm performance and CEO pay. The third assumption will be that sampled data are normally distributed among TSX/S&P and NYSE populations. The fourth assumption will be that sampled data obtain a 95 percent confidence interval. The fifth and final assumption will be that statistical results leads to either accept or reject the null hypothesis.
1.12 SUMMARY OF THE CHAPTER The CEO cash compensation topic has not been extensively researched nor has been studied on a comparative basis among Canadian and American companies. Most of the previous studies have lacked in recent research such as from 2005 to 2010. In addition, over the past decade in Canada and the United States, the public has raised concerns over bonuses declared to CEOs by companies’ board of directors. That is, CEOs should not be rewarded with bonuses if company performance is negative. As such, this research study will try to understand the nature and extent of the relationship between
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CEO cash compensation, firm size, firm performance, and CEO power, among TSX/S&P and NYSE indexes companies, from 2005 to 2010.
This research is historical, empirical, numerical, evidential, and objective based as such, quantitative research method will be selected. Within a quantitative research framework, a longitudinal study approach will be adopted to collect data from 2005 to 2010. The stratified sample method will be selected for this research study since it requires equal stratum and avoid selection bias towards determining sample sizes. The survey method will be selected to collect data of two hundred and forty companies. This research study will consist of three research questions. The first research question is: among TSX/S&P and NYSE indexes companies, what relationship is there between CEO cash compensation and firm size?. The second research question is: among TSX/S&P and NYSE indexes companies, what relationship is there between CEO cash compensation and firm performance?. The third research question is: among TSX/S&P and NYSE indexes companies, what relationship is there between CEO cash compensation and CEO power?.
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CHAPTER TWO LITERATURE REVIEW
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CHAPTER TWO - LITERATURE REVIEW 2.1 PURPOSE OF THE RESEARCH The purpose of this research is to understand the nature and extent of the relationship between CEO cash compensation, firm size, firm performance, and CEO power. This chapter will describe, summarize, evaluate, and clarify previous studies on firm size, firm performance, and CEO power. The agency theory will be discussed to understand the theoretical impact of principal and agent relationship on CEO compensation.
2.2 CEO COMPENSATION THEORIES 2.2.1 CEO Compensation and Agency Problems Agency theory deals with the relationship between a principal (shareholder) and an agent (company’s CEO or managers). It tries to resolve problems arising from a conflict of goals and desires between them. It tries to resolve a problem of a principal’s inability to verify an agent’s output. It tries to resolve a problem of risk sharing which arises when a principal and an agent have different attitudes towards risk. In addition, it points towards minimizing the moral hazard problem between owners and managers by way of control. However, since the monitoring is costly, the owners’ then try to develop incentive contracts to align their interest with those of employee managers. According to Jensen & Meckling (1976), agency theory is directed at the ubiquitous agency 40 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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relationship, in which one party, the principal, delegates work to another party, the agent, who performs that work. Thus, it attempts to describe this relationship using the metaphor of a contract.
The compensation plans are a form of contract designed to link the goals of shareholders with those of the CEO or other key executives. According to agency theory, compensation plans should be designed so that managers have sufficient incentives to make decisions that maximize shareholder wealth and thus, reduce manager shareholder agency problem. Watts and Zimmerman (1978) pointed out that CEO compensation contract may be viewed as an important means of resolving this conflict, in particular, compensation plans may be designed to maximize shareholder returns by tying pay to performance. However, Dalton, Hitt, Certo and Dalton (2007) argued that there is a potential for managerial mischief when the interests of the firms’ owners (principals) and managers (agents) diverge. This is explained in the earlier study conducted by Jensen and Meckling (1976), who believed that the conflict between them may arise because the shareholders’ primary goal is to receive maximum returns for their investments, while managers may have a wider set of preferences. According to Eisenhardt (1989), CEO compensation is influenced by agency theory in the form of governance structure whereby a weaker governance structure leads to relatively greater CEO compensation. That is, it is believed that CEO will act on his best interest by adopting a maximum power approach through controlling board and taking advantage 41 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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of operational expertise then rely on the firm’s performance. Similarly, Pratt and Zeckhauser (1985) argued that because agents control organizational resources and are likely to know more about the tasks that they perform for the principal, information asymmetry that exists could give advantage to agents. On the other hand, the principal usually wishes to counter this asymmetry and seeks to devise ways to prevent agents from making decisions to divert resources away from the principal’s interests. This is supported by Jensen (1983), who believed that principals define the rule of the game for senior management team including a system for monitoring and reward structure which includes the degree to which managerial incentives are aligned with the interests of the owners. Jensen and Meckling (1976), Fama (1980), and Hart (1983) believed that agency problems are controlled by the market for corporate control, managerial labor market, and product market control.
Finkelstein and Boyd (1989) argued that the balance of power between the board and CEO is a major determinant of CEO compensation. This is explained by Core, Holthausen and Larcker (1999), who believed that weaker governance structures have greater agency problems, CEOs at firms with greater agency problems receive greater compensation, and firms with greater agency problems perform worse. This is supported by Bebchuk and Fried (2005), who stated that executive compensation is consistent with executives who control their own boards and maximize their own compensation subject to an outrage constraint. Similarly, Weisbash (2007) stated that 42 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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contracts that are negotiated between CEO and board are not likely to be those that maximize shareholder profits subject to the usual constraints in principal agent problems; rather contracts are likely to reflect optimal rent grabbing by the CEO. Thus, focus of agency theory is on determining the most efficient contract governing principal agent relationship. 2.2.2 CEO Compensation and Agency Contracting The theoretical work on agency contract (e.g. Demski & Feltham, 1978; Harris & Raviv, 1979; and Shavell, 1979) indicated that when agent efforts are not observed by principal and information asymmetries are high, the principal has little option but to transfer risk to the agent by basing agreement on observed performance outcomes. Thus, in the absence of good information about activities or behaviors of the agent, incentive alignment is a most viable control mechanism to reduce agency costs because it engenders self-monitoring on the part of the executive (Conlon & Parks, 1990; Eccles, 1985; Eisenhardt, 1985, 1988; Fernie & Metcalf, 1986; Gomez-Mejia, 1997; Welbourne, Balkin & Gomez-Mejia, 1995). Eisenhardt (1989) stated that focus of principal agent literature was on determining optimal contract, behavior versus outcome between principal and agent. In addition, he believed that when outcome uncertainty is low, costs of shifting risk to the agent is also low and thus, outcome based contracts become attractive. This is supported by Bloom and Milkovich (1998), who believed that outcome based compensation contracts solve the agency problem even though the contract is 43 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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not an ideal solution because a pay for performance linkage necessarily transfer some risks onto a risk-averse agent. Similarly, he also believed that, as uncertainty increases, the outcome based contracts became increasingly expensive to shift risk to the agent, despite motivational benefits of it. This is further supported by Jensen and Murphy (1990), who believed that optimal compensation contracts are to provide better risk sharing without reducing incentives or to provide better incentives without increasing risk exposure. In addition, they also believed that optimum contracting arrangements may offer large amounts of compensation for executives to enhance shareholder value. On the other hand, Holmstrom (1979) believed that optimal compensation contracts for risk averse CEOs are based not only on principal objective (i.e., change in shareholder wealth) but also on any variable which provide incremental information valuable in assessing the CEO’s unobservable choice of action. Similarly, Jensen and Murphy (1989) finds that there are inconsistencies towards formal agency models of optimal contracting. That is, the empirical relationship between pay of top level executives and firm performance, while positive and statistically significant, is small for an occupation where incentive pay is expected to play an important role. This is supported by Tosi, Werner, Katz and Gomez-Mejia (2000), who believed that optimal contracting may not be realized due to the methodology used in performance measurement doesn’t properly measure the performance construct on which agency contract is based. In addition, they stated that the board of directors might well turn to performance measures that include objective indicators as well as judgmental, clinical, and subjective assessments that are 44 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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related to the job. Such criteria are more likely to represent a holistic and comprehensive assessment of executive performance. Thus, the objective performance measures find in executive compensation literature may be deficient for evaluation purposes by those responsible for corporate governance, which in turn then use a subjective evaluation process to assess the executive’s contributions. This is further supported by Mirrlees (1976), Holmstrom (1979), Lazear and Rosen (1981), Grossman and Hart (1983), Lambert (1983), and Murphy (1986), who stated that agency costs are minimized when CEO compensation is related to firm performance of other types of information regarding actions taken by executives. 2.2.3 CEO Compensation and Agency Theory According to Tosi and Gomez-Mejia (1989), who believed that agent will attempt to minimize risks and transfer all costs of uncertainty to principal. Harris and Raviv (1979) argued that the agents (managers) will prefer a weak monitoring system so to create lower risk situations for his compensation. This can be achieved by way of decoupling of pay from performance through organizational policies and practices such as, widely dispersed equity holdings and managerial control over the board of the directors. This then leads to managers designing a compensation structure in which they minimize the risks. In addition, this will permit them to choose courses of action that are in their selfinterest, even if they conflict with the welfare of the owners (Demski, Patell and Wolfson, 1984). Seville (1979) believed that there are potential gains to monitoring, except in the 45 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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unlikely situation in which the agent’s actions cannot have negative consequences for the owner. Holmstrom (1979) believed that while perfect monitoring may be impossible or too expensive, imperfect information can be used to alleviate the moral hazard by penalizing the agent’s dysfunctional behavior. Herman (1981) believed that there is more monitoring and incentive alignment in owner controlled firms than in management controlled firms. The board will represent the owner’s interests because owners will be more influential in the selection of board members. In the management- controlled firms, the board appointments will be controlled by management, and the members will serve at its discretion. In addition, he also believed that if monitoring and incentive alignment increase CEO compensation risk, then there must be a shift in the balance of power from agent to principal. Thus, the level of monitoring and incentive alignment should be inversely related to CEO pay. However, Dalton et al. (2007) argued that evidence regarding chief executive officer (CEO) compensation as a monitoring mechanism remains unsettled. 2.2.4 CEO Compensation and Agency Theory and Risk Harris and Raviv (1979) argued that managers will want their compensation structured so that they minimize personal risk. This is supported by Jensen and Meckling (1976), who argued that in order to reduce their compensation risk, managers may engage in activities which reduce the firm’s risk such as by undertaking low risk projects, which in turn adversely affect shareholders’ wealth. On the other hand, shareholders would like 46 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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to reduce their investment risk by holding a diversified portfolio. Such conflicting strategies of both parties lead to compromising agreement in the form of agency contract whereby the principal and agent established unified organizational goals and compensation mechanism. Similarly, Jensen and Murphy (1990) believed that “managerial decisions designed to strengthen organizations often meet with opposition from colleagues, employees... providing managers with incentives to compromise their decisions.”
Lewellen et al. (1987) believed that compensation packages are designed such that agency costs are reduced. In addition, they believed that compensation contract is aimed at controlling risk exposure and limiting agency problems. Furthermore, executives in the management controlled firms can reduce their risk and force owners to bear more because they have greater control over organizational decision processes. Jensen and Meckling (1976) and Lambert and Larker (1984a) argued that CEOs are risk avoiders who prefer not to jeopardize their tenures. In addition, they argued that managerial preferences and actions are aligned in such a way that agency costs are reduced. According to Holmstrom (1979), Garen (1994), Bloom and Milkovich (1998), and Aggarwal and Samwick (1999), risk shifting associated with outcome based contracts often result in higher overall compensation for the agent. Similarly, Gray and Canella (1997) argued that transferring risk from principal to agent by linking a portion of the agent’s (CEO) income to firm performance, may be less effective or even 47 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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dysfunctional towards maximizing shareholder wealth. That is, the CEO’s risk bearing making it less likely that he will invest firm resources in a risk neutral manner or engage in strategies congruent with shareholders’ preferences. John and John (1993) argued that when agency costs are high, stockholders wealth sensitivity may be lower to avoid risk shifting incentives to executives. Miller, Wiseman and Gomez-Mejia (2002) argued that if the agent's performance uncertainty increases, agent has less control over outcomes as such, agents are pushed to adopt risk reduction strategies which minimize the shareholders’ interests. In addition, agent decisions become less reliable to the point of the principal cannot rely on outcome based controls as an adequate substitute. 2.2.5 CEO Compensation and Agency Theory and Equity Ownership Fame & Jensen (1983) and Jensen & Meckling (1976) believed that firms aligned owner and agent's interests through the agents’ equity ownership and structure of their compensation. This is supported by Dalton et al. (2007) who believed that the agent’s equity ownership leads to embrace shareholder interests. Nyberg, Gerhart and Carpenter (2010) defines incentive alignment as financial alignment, whereby an agent’s economic reward co-vary with those of owners through ownership structure. However they find that the relationship between financial alignment and future shareholder return is not contingent on CEO stock ownership. This finding is also supported by Tosi, Werner, Katz and Gomez-Mejia (2000) and Dalton et al. (2003), who finds that there is no relationship between CEO equity ownership and organization 48 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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performance. That is, there is little evidence to support agency theory emphasis on alignment between the financial interests of principal and agent preferences and actions through equity ownership. 2.2.6 CEO Compensation and Productivity Theory According to Shetty, Mithiun (2012), marginal productivity theory is mainly concerned with predicting the pay levels of executives. The practical implication of marginal productivity theory is that both the firm’s profitability and the executive’s relative economic contribution are pay-level determinants. He believed that executive compensation theories are made with a context of analyzing the firm’s ability to generate profits and maximize productive output. His research concluded with two propositions. Firstly, he believed that the size of the executive pay package reflects the firm’s net profits. In a firm where the entrepreneur is the sole owner and functions as chief executive officer, the entrepreneur desires to achieve the highest returns on his investments and this will occur where the marginal cost of production is equal to the market price of the product. That is, a point where the firm maximized its profits and CEO maximized his compensation. Secondly, he believed that the size of the executive pay package is proportional to the executive’s marginal revenue product. In addition, it is assumed that the executive is hired by the firm and his pay commensurate with his economic contribution. Therefore, the theory predicts a convex relationship between the compensation gap and the number of contestants competing for promotion. This is 49 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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supported by Zang and Masulis (2012), who finds that executive compensation is strongly linked to measures of senior executive productivity, and that productivity differentials among senior executives explain a large part firm compensation gaps. In addition, they believed that executives whose managerial ability is recognized by the external labor market are expected to exhibit higher productivity than executives whose abilities go unrecognized. 2.2.7 CEO Compensation and Tournament Theory ! !
The tournament theory emphasizes that job hierarchy provides incentives to employees and firms use promotions as a mechanism of rewarding strong employee performance. Rosen and Lazear (1981) treats pay as a prize in a contest. First prize in the tournament is the highest pay received by the CEO, the highest-ranking position in an organization. Setting a high prize provides incentives for the contestants to climb higher on the corporate ladder (Rosen, 1986) and indirectly increases the productivity of competitors at lower levels (Balsam, 2002). When the top price is set at a disproportionately high level it has the effect of lengthening the career ladder of high ranking managers (O’reilly, Main, and Crystal, 1988). According to Rosen (1986): “Contestants who succeed in attaining high ranks in elimination career ladders rest on their laurels in attempting to climb higher, unless top-ranking prizes are given a disproportionate weight in the purse. A large first-place prize gives
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survivors something to shoot for, independent of past performances and accomplishments”.
Wade, Main, and O’Reilly (1993) finds that more competitors increases the competition gap between a CEO and lower level executives. Zang and Masulis (2012) finds that tournament theory predictions are not strengthened when include periods prior to the departure of incumbent CEOs or firms most prone to succession contests. That is, the effects of the variables capturing tournament competition, the coefficients of the tournament intensity variables are insignificantly different than levels found in estimating the remaining firms. Furthermore, the overall explanatory power of variables is much lower than that of variables measuring executive productivity in the tournament-oriented firms.
Zang and Masulis (2012) believed that the tournament effect is likely to be more pronounced in shaping executive compensation when a CEO replacement is expected due to planned retirement. Companies are mostly likely to have a well-planned CEO succession strategy and run a contest among potential candidates when the incumbent CEO is approaching mandatory retirement age. In addition, they believed that in situations where CEOs are forced to resign due to extremely bad performance, the hiring of new CEOs is less likely to depend on the result of succession contest. This is due to, firstly, the urgency associated with extremely bad firm performance, a board of 51 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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directors has little time to select a new CEO. Thus, a non-CEO officer director or the chair of the board may step in as an interim person. Secondly, bad firm performance is an indicator of a poorly performing management team, which means a board of directors would be more likely to seek an outsider as the CEO to turn around the current negative performance. Therefore, perhaps a stronger tournament effect on the compensation gap prior to a planned retirement than a forced CEO turnover due to bad performance. 2.2.8 CEO Compensation and Agency Theory and CEO Power The executive compensation is viewed as a solution to shareholders’ optimal contracting problem. That is, the CEO contract is designed by shareholders or their representatives to maximize shareholder value. In a series of articles written by Bebchuk and his co-authors (Bebchuk et al., 2002; Bebchuk and Fried, 2003, 2004) challenge this view and believed that practice of executive pay is explained better by the managerial power theory whereby CEOs effectively set their own pay by influencing the pay-setting process. That is, the managerial power theory argues that because of principal agent relations, agents are in the natural position to use their discretion to set their own pay. In addition, they believed that managerial power theory refers to the mechanism whereby the management, even with negligible share ownership, can assume effective control of the firm through the appointment of the proxy committee, which they dub management control. Finkelstein (1992) describes the various 52 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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dimensions of managerial power, of which, the ability to affect one’s own pay are one dimension of managerial power, a structural power. Therefore, the most powerful CEOs receive high pay or award themselves with few conditions. This indeed has a negative effect on the pay-performance sensitivity of CEO compensation indicating managerial power leads to worse firm performance. Fama and Jensen (1983) believed that executives are in the position to use their power to influence the board of directors to keep them in check. In contrast to the complete contracting theory, natural relationships between principals and agents and the consequent possible use of discretion are considered as real possible behavior (Grabke-Rundell and Gomez-Mejia, 2002).
According to Yin, Tian, and Chow (2008), the managerial contract is determined through bargaining between the board and the manager. They believed that, where the board has full bargaining power, the board designs a compensation contract for the manager to maximize the shareholder’s residual return subject to the manager’s incentive compatibility, individual rationality, and limited liability constraints. On the other hand, where the manager has full bargaining power, the manager designs his own compensation contract to maximize his expected utility subject to the shareholder’s individual rationality constraint, his own limited liability and incentive compatibility constraints. The solution to a general bargaining problem lies between these two scenarios, varying continuously in some proxy of the manager’s bargaining power. In addition, they believed that when the manager designs a compensation contract for 53 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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himself, he would do so to motivate himself to exert an efficient level of effort that would maximize the expected return. He can then extract the entire surplus from the shareholder through a lump sum base salary for himself, making the shareholder’s individual rationality constraint binding in the process. If the board designs the managerial contract, it would again motivate the manager to exert the efficient level of effort, despite the manager in this scenario would not enjoy the entire surplus. Therefore, whoever designs the contract faces the same optimization problem. This concept is also supported by Finkelstein, 1992; Pfeffer, 1992; Adams et al., 2005.
According to Yin et. al (2008), in determining the optimal managerial contract, a bargaining game between the owner and the manager happened. The bargaining game proceeds given the two reference points, one based on agency theory and the other based on managerial power theory. If the owner has all the bargaining power making a non-negotiable offer to the manager as is typically assumed in agency theory, the resulting contract is the one that maximizes the owner’s expected utility subject to the manager’s individual rationality and incentive compatibility constraints. If the manager has all the bargaining power in contract design, then the resulting outcome is the contract that maximizes the manager’s expected utility subject to the owner’s individual rationality constraint and the manager’s incentive compatibility constraint. In firms where the manager’s base salary is positive and unconstrained, both the size of the manager’s stock-based compensation and the pay-performance sensitivity of management 54 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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compensation are independent of managerial power. In firms where salary is no longer the vehicle through which the powerful manager can fully extract rent from the owner, stock-based compensation is used as an additional channel for rent extraction. That is, the manager awards himself more stock-based compensation when there is a salary ceiling, which increases his income risk and effort incentives. In addition, larger stockbased compensation for the manager implies that the pay-performance sensitivity of managerial contract should also be higher in firms where the manager has more power.
Hope and Thomas (2008) have documented that the influence of insiders, in this case the CEO, will also be a function of the degree of outside institutional ownership shares that hold a controlling interest in the firm. Offsetting this effect, the more shares owned by independent agents, the less will be the CEO's influence on director elections and the more vulnerable the CEO will be to a hostile takeover attempts. Thus, the influence of the CEO increases proportionally to the percentage of shares they own. Starks, Hartzell, and Almazan (2008) believed that the professional reputation is particularly crucial to outside directors who typically aren't joining a board for pay. In some cases where remuneration isn't involved, outside directors join corporate boards for the prestige the membership gives them. Hence, outside directors would be hesitant to construct a compensation plan that would negatively affect their reputations. As a result, outside directors will support management only as long as the compensation contract does not impose too much outrage cost. Holden (2008) believed that the reduction in 55 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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shareholder value caused by CEO compensation contract inefficiencies is likely the biggest cost arising from the influence of managerial power on compensation practices. Thus, improvement in this corporate control area should provide considerable benefits to shareholders from better managerial incentives, firm operations and performance.
According to Finkelstein and D’Aveni (1994), managerial power theory predicts that the concentration of decision-making power in one individual leads to more power, for several possible reasons. They believed that CEO duality plays complementary roles in managerial power theory. First, it typically increases the CEO’s discretionary powers over firm resources and is thereby taken by inside and outside stakeholders reflecting strong leadership. The figurehead CEO/Chair tends to present him or herself as the ulterior representative of the corporation, and typically seeks to underwrite this status and mandate with higher than average pay (Gomez-Mejia, 1994). Second, in a situation of duality, the CEO, as leader of his fellow collaborating executives, is also the leader of the board, and can therefore command additional obedience and loyalty on behalf of those entities that are put in place to set executive pay (Bebchuk and Fried, 2004). Third, the dual role of CEO and chairman can be considered as the highest rank in the corporate hierarchy. This figurehead status, with more mandate and power, can lead to more influence over the pay setting process (Ungson & Steers, 1984).The CEO duality allows executives to extract greater rents from the corporation in countries offering relatively weak protection against managerial self-dealing like the US (Djankovet al., 56 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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2005). In addition, the United States studies have repeatedly shown that there is a positive relationship between pay and duality (Boyd, 1994; Main and Johnston, 1993; Westphal and Zajac, 1995).
According to Bebchuk and Fired (2003), the length of a CEO’s tenure is also likely to be an important determinant of managerial power. Longer tenured CEOs can be expected to have more influence over board members and their decisions because they have more status and more experience with the company and its board. The collaboration among board members and collegial bonds intensify over time, and CEOs with longer tenure have more time to influence this process (Bebchuk & Fried, 2004). The CEOs with longer tenure can also be more influential over the remuneration committee directly. The remuneration committees whose chairs have been installed later than the CEO tend to pay more (Main et al., 1995).
According to Zahra and Pearce (1989), the size of the board in terms of the number of directors is also likely to enable or constrain managerial power. Although monitoring requires capacity, large boards can be ineffective at constraining managerial power because larger boards require more time and effort to build consensus and generate the social cohesion of smaller boards. In addition, larger boards can become ineffective because of internal coordination and communication problems (Bebchuk & Fried, 2004). Therefore, according to O’Reilly & Main (2010) and Pfeffer, (1972), the in-group 57 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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monitoring and collective action problems of larger boards may provide executives with more power over the pay-setting process.
According to Bebchuk and Fried (2004), the composition of the board in terms of the percentage of independent directors may also influence managerial power. The directors are considered independent if they are not currently or have never been employees of the company and have no other relationship with the firm, such as business contracts. However, they highlighted a number of ways that independent directors can actually lose independence and become vulnerable to managerial influence, such as the role of CEOs in director selection, the close connections and bonds of shared interests and collegiality among board members, and the dependence of independent directors on managers for information. Moreover, the collaboration among independent board members and managers may intensify over time. In such situations, independent directors can become less willing to challenge executive compensation arrangements.
According to Tosi et al. (2000), the managerial power theory argues that the ownership structure of the corporation can enable or constrain the power of CEOs. For example, large, concentrated owners often have both the means and incentives to monitor management effectively (Bebchuk & Fried, 2004). More specifically, since these
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owners have large investment stakes, they are more dependent on the performance of the firm. In addition, large owners are more able to protect their interests by means of both formal influence, such as the nomination of and voting for directors, and informal communication with the management (Smith, 1996). In contrast, for dispersed shareholders, who own only a small percentage of a firm, the costs of close monitoring may be too high relative to the possible gains produced by such monitoring. In addition, dispersed shareholders are likely to have dispersed strategies and goals for increasing firm value, leaving management with more influence to make their own calls (Thomsen and Pedersen, 2000). In addition to the concentration of ownership, the identity of a firm’s owner can also constrain or enable managerial power over executive compensation practices. Although their status as institutional investors does not give them more formal power than other investors, they often have substantial holdings and fiduciary obligations to their investors to improve the returns to their clients. Therefore, institutional investors tend to more actively monitor management than individual investors and may be more able to constrain the executive power in setting compensation (Bebchuk & Fried, 2004).
According to Gomez-Mejia (1994), a theory that extends managerial power theory is class hegemony theory. This theory argues that executives within a firm and executives from other firms share a commonality of interests. Where managerial power theory
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stops at the boundaries of firms, class hegemony theory extends managerial views beyond these boundaries. Shared interests and objectives to create bonds between executives that extend beyond a single organization. These bonds form relationships which in turn forms a class across different organizations. By using this shared power the executives can protect their privileges and the wealth of their class. Although primarily executives’ input is used to legitimize high executive pay, setting high pay is also a token of executives’ power to protect shared interests and objectives. Setting executive pay is thus a result of the social managerial class’s power to protect their interests and objectives that are at potential risk. 2.2.9 CEO Compensation and Stewardship Theory and CEO Power Stewardship Theory has been framed as the organizational behavior counterweight to rational action theories of management (Donaldson and Davis, 1991). This theory holds that there is no conflict of interest between managers and owners, and that the goal of governance is, precisely, to find the mechanisms and structure that facilitate the most effective coordination between the two parties (Donaldson, 1990). That is, this theory holds that there is no inherent problem of executive control, signifying that organizational managers tend to be benign in their actions (Donaldson, 2008). The stewardship theory defines the situations in which managers’ motives are aligned with the objectives of their principals, rather than motives of individual goals. It argues that stewards place higher value on co-operation and thus perceive greater utility in 60 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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cooperative behavior. The essential assumption underlying the prescriptions of stewardship theory is that the behaviors of the manager are aligned with the interests of the principals. A steward’s utility function is maximized when the shareholders’ wealth is maximized (Davis et al., 1997). The steward perceives that the utility gained from interest alignment and collaborative behavior with the principal is higher than the utility that can be gained through individualistic, self-serving behaviors (Davis et al., 1997). Stewardship theory places greater value on goal convergence among the parties involved in corporate governance than on the agent’s self-interest (Van Slyke, 2006). The stewardship theory assumes a strong relation between the firm’s success and principal satisfaction. This theory, a sociological and psychological approach to governance, hinges on the assumption that executives feel a strong sense of attachment to and psychological ownership of their firm, and hence are more likely to behave as stewards. This perspective stands in marked contrast with agency theory in which managers are assumed to act in their own interest at the expense of shareholders. Higher levels of ‘psychic income’ (Gimeno, Folta, Cooper, and Woo, 1997) should make such ‘organizationally centered’ executives accept lower cash compensation to continue working in the organization (Davis, Schoorman, and Donaldson, 1997).
Stewardship theory argues that there is no general executive motivation problem, because executives act as true stewards of the firm, in pursuit of organizational goals. 61 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Executive pay plays a secondary role in executive motivation, because non-financial rewards are of more importance (Donaldson et al., 1991). It focuses more on intrinsic, rather than extrinsic rewards. The executives are intrinsically motivated by the need to achieve and to receive recognition from others. The executive pay could be legitimized by arguing that it is merely a relatively minor part of executive motivation and forms only part of the recognition that executives receive for being stewards of the firm. In addition, it argues a contradicting view of CEO power (Davis et al., 1991). However, it does not provide a-priori clear hypotheses about pay levels or pay structures and could therefore be questioned as a useful theory to legitimize executive pay. In the economics and finance literature, the stewardship theory has never been regarded as a valid alternative to agency theory, has not lead to practical managerial decision rules, and has gained little empirical support. Davis et al. (1997) states that stewardship views are addressed because the theory does attempt to explain that executive pay does not have to be strongly related to shareholder wealth or other measures of the firm’s financial performance. Using sociological and psychological approaches, stewardship theory sees subordinates as collectivists, pro-organizational and trustworthy relative to agency theory, which assumes subordinates to be individualistic, opportunistic, and self-serving Donaldson (1995). In the psychological aspect, there is the use of power. It is meant that managers receive satisfaction from the use of power and are therefore motivated by it (McClelland, 1975). 62 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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The power motive is defined as the need to influence others to achieve organizational goals (McClelland and Burnhan, 1976). According to Davis et al. (1997), power is institutionally and personally based. Where institutional power means that principal exert control based on its position in the organization by identification of the principal to the organization. Davis et al. (1997) argues that coercive legitimate and reward power could be seen as institutional power. On the other hand, personal power is based on an intrinsic abilities and interpersonal relationships. Davis et al. (1997) explains that expert and referent power are typical for personal power where referent power is created through identification between individuals. This type of power is not affected by organizational structure and formality. For the principal-steward relationship with the stewardship theory, personal power is vital.
2.3 CEO COMPENSATION AND FIRM PERFORMANCE 2.3.1 CEO Compensation and Pay Structure Koplyay et al. (1992) reported that top Canadian managers get 35-50% of their pay in the form of incentives while the United States CEOs get 50-75% of their pay in the form of incentives. In addition, they reported that the average Canadian CEO took 30% of total pay in the form of bonus, and 11% of total pay in the form of stock purchase plans or stock options. Mehran (1992) reported that CEOs took 67% of total pay in the form of salary and bonus, and 22% in the form of equity based incentives. This study is based 63 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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on two year period. In addition, Mehran’s another study conducted in 1995 finds that nearly 74% of CEOs’ compensation are in salary and bonus. This study is based on one year period. Agarwal (1981), Finkelstein and Boyd (1998), and Finkelstein and Hambrick (1989,1996) concluded that a simple measure of cash compensation is an excellent proxy for CEO total pay. This is supported by Douglas & Santerre (1990) and Gomez-Mejia, Tosi and Hinkin (1987), who reported that an average “R” (regression) between salary and total compensation of 0.75 in the sample of k (years)=8, and n=1400 (companies). However, they find that most of previous studies have used CEO total compensation (CEO compensation)5 relative to CEO cash compensation6 as a dependent variable in their studies. This is perhaps due to, third party data are either available mostly on the CEO total compensation basis or researchers are not interested in segregating short and long terms aspects of the CEO compensation system. As such, CEO cash compensation has rarely been studied with firm performance. Nevertheless, previous studies have found that CEO cash compensation is an excellent proxy for CEO total compensation.
5 CEO cash compensation, stocks, options, pensions, and other benefits. 6 CEO salary and bonus.
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2.3.2 CEO Compensation and Firm Performance Linkage According to previous studies conducted in the United States and the United Kingdom, CEO compensation is believed to be weakly related to firm performance. Loomis (1982) argued that pay is unrelated to performance. Henderson and Fredrickson (1996), and Sanders and Carpenter (1998, 2002) argued that CEO total pay may be unrelated to performance but it related to organizational complexity they manage. Likewise, studies conducted by Murphy (1985), Jensen and Murphy (1990), and Joskow and Rose (1994) find similar conclusions.
Jensen and Murphy (1990) argued that incentive alignment as an explanatory agency construct for CEO pay is weakly supported at best. That is, objective provisions of principal agent contract are not comprehensive enough to effectively create a direct link between CEO pay and performance. They find that pay performance sensitivity for executives is approximately $3.25 per $1000 change in shareholder wealth, small for an occupation in which incentive pay is expected to play an important role. This is supported by Tosi, Werner, Katz and Gomez-Mejia (2000), who finds that overall ratio of change in CEO pay and change in financial performance is 0.203, an accounting for about 4% of the variance. This weak relationship is explained by Borman & Motowidlo (1993) and Rosen (1990), who stated that archival performance data focuses only on a
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small portion of a CEO’s job performance requirements. As a result, it is difficult to achieve a robust conclusion.
According to Jensen and Murphy (1990) who believed that CEO bonuses are strongly tied to an unobservable performance measure. They believed that if bonuses depend on performance measures observable only to the board of directors, they could have provided a significant incentive. They believed that one way to detect the existence of such phantom performance measures are to examine the magnitude of year to year fluctuations in CEO compensation. They believed that such fluctuations signify CEO pay is unrelated to accounting performance. In addition, they argued that although bonuses represent 50% of CEO salary, such bonuses are awarded in ways that are not highly sensitive to performance. And the variation in CEO pay can be explained by changes in accounting profits than stock market value. Overall, they believed that pay performance sensitivity remains insignificant.
Jensen and Murphy (1990) finds in their study that CEO received an average pay increase of $31,700 in years when shareholders earned a zero return, and received an average additional 1.35¢ per $1,000 increase in shareholder wealth. These findings are comparable to those of Murphy (1985,1986), Coughlan and Schmidt (1985), and Gibbons and Murphy (1990), who finds that pay performance elasticity of approximately 0.1, signifying, salaries and bonuses increased by about one percent for every ten 66 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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percent rise in the value of the firm. In addition, they find an average pay increase of CEOs whose stockholders gains $400 million is $37,300, compared to an average pay increase of CEO whose stockholders lose $400 million is $26,500. These findings are supported by Jensen and Murphy (1990), who believed that CEO cash compensation should be structured to provide big rewards for outstanding performance and meaningful penalties for poor performance. In addition, they believed that the relationship between CEO cash compensation and firm performance would be less troubling if CEO owned a large percentage of corporate equity. Gilson and Vetsuypens (1993) argued that the association between pay and performance is small in economic terms when performance is measured in terms of changes rather than levels. This is supported by Iyengar (2000) who argued that changes in CEOs compensation are unrelated to changes in firms’ performance perhaps due to stockholders in poorly performing firms would like to adopt a cautious wait and see attitude, to assess whether a change in performance is permanent before rewarding senior managers. This is further supported by Antle and Smith (1986), who finds no relation between CEO cash compensation and firm performance. However, these statements are contradicted by Jensen and Zimmerman (1985), who stated that evidences are inconsistent with a view that executive compensation is unrelated to firm performance and enriches managers at the expense of shareholders. This is supported by Gibbons and Murphy (1990), who finds that CEO pay changes by about 1.6% for each 10% of return on common stock. That is, the CEO pay structure is positively and significantly related to firm performance, 67 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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as measured by the rate of return on common stock. This is supported by Lambert and Larcker (1987) and Sloan (1993), who finds that there is a positive relation between CEO compensation and stock returns. According to Blanchard, Lopez-de-Silanes and Shleifer (1994), Iyengar, Raghavan J. (2000), and Bertrand and Mullainathan (2001), who stated that CEO cash compensation increases when firm profits rise for reasons that have nothing to do with managers’ efforts. Murphy (1986) believed that top executives are worth every nickel they get.
McEachern (1975), Allen (1981), Amould (1985), Gomez-Mejia, Tosi, and Hinkin (1987), Dyl (1988), Gomez-Mejia and Tosi (1989), and Kroll, Simmons and Wright (1989), believed that the relationship between executive pay and performance may be stronger in owner-controlled than management-controlled firms. Werner and Tosi (1995), who finds in their study that managers in widely held firms are paid more than managers in closely held firms. Dyl (1988) argued that there is a downside hedge in compensation of CEOs in management-controlled firms, provided it is more related to firm size than performance. According to Hunt (1986), several studies have shown owner-controlled firms are more profitable; several studies have shown management- controlled firms are more profitable; and other studies have shown no differences. As a result, he believed that perhaps these inconsistent results could be different uses of accounting performance measures in previous studies.
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Williamson (1963) argued that vigilant directors do not suppress CEO compensation as much as they try to tightly link it to the firm’s performance. In addition, he believed that directors strive to reward high performance and penalize low performance, their own attempt to induce managerial actions aimed at maximizing shareholder wealth. Mehran (1995) finds that companies in which CEO compensation is relatively sensitive to firm performance tend to produce higher returns for shareholders than companies in which the relationship between CEO pay and performance is weak. Gaver et al. (1995) and Holthausen et al. (1995a), who believed that executives managed earnings downward when reported performance exceeds contract and they managed earnings upward when reported performance is below threshold. In addition, they may also smooth the performance in the incentive zone if pay for performance relation is concave above standard (Indjejikian and Nanda, 2002). Sanders and Carpenters (1998) and Finkelstein and Boyd (1998) believed that firm performance is only one of many influences that impact CEO pay. That is, the CEO contract encompasses a complex set of factors such as, outcome measurability (Eisenhardt, 1985, Fernie and Metcalf, 1996, Gomez-Mejia and Balkin, 1992); outcome uncertainty (Eisenardt, 1985,1988); information systems (Eccles, 1985); time (Conlon and Parks, 1990); information asymmetries (Henderson and Frederickson, 1996); and task programmability (Eisenhardt, 1985).
Healy (1985), Lambert and Larcker (1987), Pavlick et al. (1983), and Verrechia (1986) believed that incentive scheme based on accounting performance measure appear to 69 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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influence accounting earnings. Porac and Pollack (1997) finds that when accounting returns are high then firm downplay market returns. However, Lambert and Larcker (1987) argued that firms place relatively more weight on market performance than on accounting performance measure in compensation contracts for situations in which variance of accounting performance measure is high relative to market performance measure, when the firm is experiencing high growth rates or managers holding of the firm’s stock is low. However, Gibbons and Murphy (1989) argued that basing compensation on accounting performance distorts CEO incentives. That is, paying executives based on accounting profits rather than changes in shareholder wealth not only manipulates accounting results, but also ignore projects with large net present values in favor of less valuable projects. This is supported by Ronen and Sadan (1981), who argued that corporate managers often engage in income smoothing, taking actions to dampen fluctuations in their firms’ publicly reported net incomes. This is supported by Trueman and Titman (1988), who stated that by smoothing income, managers may attempt to reduce estimates of various claimants of the firm therefore, will stabilize net income. Jensen and Murphy (1990) finds in their study that CEO compensation is weakly related to changes in accounting profits and sales, but is unrelated to market and industry performance. That is, the amount of CEO pays at risk for a $48 million change in accounting profits is $9,000, or less than 2 percent of compensation for CEOs with median earnings of $490,000.
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Murphy (1999) stated that bonus contracts are usually written based on accounting earnings and not explicitly on stock returns. Bushman et al. (1995,1996) reported that 40 percent of their sampled CEOs received bonuses based on individual performance evaluation which includes discretionary and subjective bonuses. However, Murphy and Oyer (2002) believed that CEOs are less likely than non CEO executives to receive discretionary bonuses. Ellig (2002) argued that accounting measures are backward looking and pertain to short term firm performance. Shaw and Zhang (2010) finds that when earnings performance is very poor, CEO’s bonus is zero. In addition, they find that CEO cash compensation is sensitive to accounting performance. That is, earnings performance improves beyond the lower bound, a linear relation between CEO cash compensation and firm performance is expected in the incentive zone. Similarly, earnings performance improves above the upper bound, cash compensation becomes insensitive to performance and therefore no bonus is further awarded. However, other researchers believed that the relationship between executive pay and performance may be stronger in owner-controlled than management-controlled firms (McEachern, 1975, Allen, 1981, Arnould, 1985, Dyl, 1988, Kroll, Simmons and Wright, 1989). This is supported by Gomez-Mejia, Tosi and Hinkin (1987), who stated that managementcontrolled firms clearly design compensation systems to avoid the vagaries of fluctuating performance. In addition, executives in management-controlled firms may be decoupled from performance through organizational policies and practices such as, widely dispersed equity holdings or managerial control over the board of directors as 71 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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such, less compensation uncertainty for CEOs (Tosi and Gomez-Mejia, 1989). Murphy (1999) reported that 62% of performance measures used in bonus contracts are accounting based and the rest is based on individual performance measures. In addition, he reported that earnings based bonus contracts often contain lower and upper bounds, suggesting reduced sensitivity of cash payments to earnings when earnings are either very high or very low. Secondly, since accounting earnings exclude unrealized gains and include unrealized losses, CEO pay will react symmetrically to accounting earnings and losses.
Lambert and Larcker (1987) and Sloan (1993) argued that CEO cash compensation may be more closely related to accounting than stock performance. This is supported by Warfield and Wild (1992), who reported that explained variance (adjusted R²) in the relationship between accounting earnings and shareholder return is .02 over a quarter period, increased to .09 over one year, and increased to .40 over four years. Natarajan (1996) finds that the cash flow measure is used to supplement accounting earnings in CEO contracts. Leone et al. (2006) argued that if the accounting system is designed solely for use in compensation contracts, then there would be no asymmetry in the relation between CEO cash compensation and accounting earnings, provided when firms have no other accounting based contracts, litigations, taxes, and accounting method of choice. On the other hand, Gilson and Vetsuypens (1993) argued that accounting earnings may be an unreliable indicator of firms’ true financial condition 72 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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because CEOs have strong economic incentives to manage accounting earnings when firms are in distress.
Holthausen et al. (1995) and Leone and Rock (2002) argued that accounting based annual bonus plans motivate executives to be more productive in the short term. In addition, they believed that target bonuses reflect ex ante intentions to motivate their executives thereby increasing firm value. Indjejikian and Nanda (2002) finds that executives’ target bonuses are negatively associated with accounting based performance metrics and positively associated with proxies for firms’ growth opportunities. In addition, they also find that firms do not fully adjust performance standards for executives’ past performance. That is, if executive previously earned more than his target bonus, then he has a 72% chance of earning more than his target bonus again in the current year. Similarly, if the executive previously earned less than his target bonus, then he has only a 42% chance of earning more than his target bonus in the current year. Likewise, they also find that executive’s expected abnormal bonus (difference between actual and target bonus) in the current period is highly correlated with abnormal bonus received in the previous period. Antle and Smith (1986) believed that the executive’s ability to hedge systematic or unsystematic risk through a compensation plan based on accounting measure is less likely than his ability to hedge such risk when compensation plan is based on market measure.
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Tosi and Gomez-Mejia (1989), authorities on executive compensation topic, stated that despite the enormous amount of efforts and expenditures in mining these public databases, the results are disappointing and often conflicting. One group of researchers has found no relationship between executive pay and firm performance (e.g., Redling, 1981, Kerr and Bettis, 1987); while another group of researchers has reached the opposite conclusion (e.g. Masson, 1971, Murphy, 1985). These opposing camps are exemplified by the conclusion of Kerr and Bettis (1987), who finds that there is no rational basis of top management compensation. Barkema and Gomez-Mejia (1998) argued that failure to identify a robust relationship between top management compensation and firm performance have led scholars into a blind alley. Tosi et al. (2000) blamed divergent results to the use of different data collection methods, different statistical techniques, different sample sizes, the presence of different moderator variables, and differences in how constructs of interest have been operationalized in various studies. In addition, they believed that previous studies rely on a traditional narrative approach which critically compares, contrasts, and integrates a large number of studies as such, have reserved the interpretation of the results to the author. Therefore, these synthetic works suffer from the same malady, while some authors concluding that firm performance are an important predictor of CEO pay (e.g., Ehrenberg and Milkovich, 1987); and others concluding that evidences fail to support such a relationship (e.g., Gomez-Mejia, 1994).
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Overall, previous studies between CEO compensation and accounting performance have not been robust as such the results have ranged from nil to weak positive correlations. These inconsistent findings are perhaps due to the selection of different sample sizes, different measurement periods, and different proxies for accounting earnings. In addition, firm size has never been used as a control variable towards understanding the relationship between CEO cash compensation and accounting earnings, in clear terms. 2.3.3 CEO Compensation and Return on Assets (ROA) Jensen and Murphy (1990) and Ely (1991) argued that applying return on assets (ROA) as a firm performance measure is considered highly important in determining executive compensation. This is supported by Finkelstein and Boyd (1998) and Finkelstein and Hambrick (1996), who have used ROA in their respective executive compensation studies. Antle and Smith (1986) finds that there is a strong correlation between CEO compensation and ROA. This is supported by Shawn and Zhang (2010), who finds that changes in CEO cash compensation is significantly and positively correlated with changes in ROA. However, from the meta analysis conducted by Tosi, Werner, Katz and Gomez-Mejia (2000), who finds that estimated correlation between CEO pay and ROA is 0.117, which accounts for less than 2% of variance in CEO pay levels. On the other hand, Mehran (1995) finds that ROA is inversely related to the percentage of
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CEOs’ total cash compensation, despite controlling for firm’s growth opportunities, assets in place, leverage ratio, business risk, and size.
Sigler (2011) argued that rewarding cash bonuses to executives may encourage the undesired behavior. That is, cash bonuses tied to accounting performance such as ROA may motivate executives to manipulate the timing of revenues and expenses. Balsam, Fan and Mawani (2011) finds in their study that CEOs of large firms (as a proxy by Sales) earned higher levels of compensation. The accounting profitability (ROA) is positively associated with total cash compensation, and the market return is positively associated with CEO salary and total compensation. Their study is based on a sample of 300 companies obtained from TSX/S&P index from 2001 to 2006. On the other hand, Leone et al. (2006) finds that there is no change in CEO pay to changes in ROA based on positive and negative stock returns. Overall, previous studies have found weak relationships between CEO compensation and return on assets. Furthermore, studies lacked extensity and robustness. Firm size has never been used as a control variable towards understanding the relationship between CEO cash compensation and return on assets, in clear terms. 2.3.4 CEO Compensation and Return on Equity (ROE) Antle and Smith (1986) have argued that common stock returns are an obvious choice to measure an executive performance. They believed that common stock returns 76 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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impound information about changes in a firm’s financial condition which are associated with both current and anticipated actions and events. In addition, most executives’ wealth is tied to stock returns directly through ownership of shares and options in their employer firms. This is supported by Leone, Wu and Zimmerman (2006), who stated that stock returns are positively correlated to CEO cash compensation. They referenced their statement to Holmstrom (1979), who explained that as long as stock returns and earnings are informative about managers’ effort, each will be used in setting CEO’s cash compensation. Mehran (1995) finds that stock return as a proxy for firm performance is most appropriate for all equity firms. In addition, he finds (1999 study) a positive correlation between stock returns and cash compensation, despite they are not contractually linked to CEO contracts. This is supported by Murphy (1985), Kren and Kerr (1997), and Murphy and Oyer (2003), who reported a positive association between executive compensation and stock returns. Leone, Shuang Wu and Zimmerman (2006) argued that CEO cash compensation is roughly twice as sensitive to negative stock returns as it is to positive stock returns. Their finding is based on data collected from 1993 to 2003. This is supported by Shaw and Zhang (2010), who finds that the relationship between changes in CEO cash compensation and stock returns for firms with negative market adjusted returns are stronger than firms with positive market adjusted returns. In addition, they find no asymmetry in CEO cash compensation for firms with low stock returns. On the other hand, Dechow (2006) believed that Leone et al. (2006) study misclassified a large number of firms with good earnings performance 77 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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as poor performance such that observed asymmetries in CEO pay is due to the Board of Directors practically applying bonus contract provisions. That is, CEOs are not penalized rather are rewarded for negative firm performance. This is supported by Garvey and Milbourn (2004), who finds that CEOs are rewarded for good luck but not penalized for bad luck, where luck is defined as a component of firm stock returns that is associated with market or industry returns. This is also supported by Jensen and Murphy (1990), Kaplan (1994), and Gaver and Gaver (1998), who find that CEO cash compensation is shielded from transitory accounting losses, and senior managers on average suffer a little reduction in their personal wealth even when their firms perform poorly. However, Barclay et al. 2005 believed that punishment for poor performance might be plausible when performance is based on returns. This is contradicted by Lambert and Larker (1987) and Sloan (1993), who find that CEO compensation is more sensitive to measures based on earnings than stock returns. This is supported by Firth et al. (1996,1999) and Gregg et al. (1993), who revealed that here is no significant relationship between earnings and stock returns. This is also supported by an earlier study conducted by Johnson (1982), who finds that ROE to be correlated with executive pay at .003. Similarly, Finkelstein and Boyd (1998) reported a correlation of -.03 between CEO compensation and ROE. On the other hand, Belliveaus, O’Reilly and Wade (1996) finds that the correlation between CEO pay and ROE is .410. Aggarwal and Samwick (1999) believed that CEO pay performance sensitivity systematically varies with stock return volatility. Nyberg, Fulmer, Gerhart and Carpenter (2010) finds 78 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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that changes in CEO compensation and stock returns are likely to be more strongly related if measurement periods and measurement components are appropriately matched, for example, short term compensation with short term accounting performance and long term compensation with long term firm performance.
Overall, previous studies between CEO compensation and return on equity have produced mixed results ranging from weak negative to good positive correlations. These inconsistent findings are perhaps due to the selection of different sample sizes and different measurement periods. Furthermore, firm size has never been used as a control variable towards understanding the relationship between CEO cash compensation and return on equity, in clear terms. 2.3.5 CEO Compensation, Stock Ownership, and Stock Price Boudreaux (1973), Plamer (1973), and Gomez-Mejia, Tosi, and Hinkin (1987) believed that a single equity holder who controls at least five percent of voting stock is characterized as an owner-controlled firm. Similarly, when there is no equity holder with at least 5 percent of the stock, firm is called management controlled firm. However, Tosi and Gomez-Mejia (1989) argued that though these five percent criteria are widely used in research studies, but it has never been shown as criteria for control or qua control. Rather, it is only used to differentiate in performance measures or organizational practices such as financial reporting. On the other hand, Jensen and Murphy (1990) and 79 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Hubbard and Palia (1995) favored performance to be measured with stockholder value to reflect CEO wealth. Murphy (1999) believed that the relationship between shareholder and CEO financial outcomes is obvious and explicit. That is, executive and shareholder returns are based on the value of the same underlying asset, company stock. Gerhart et al. (2009) believed that earnings are imperfectly related to shareholder return primarily due to firm specific wealth is generated via equity positions.
According to Jensen and Murphy (1989), CEOs in large firms tend to own less stock and have less compensation based incentives than CEOs in small firms. Murphy (1985) and Coughlan and Schmidt (1985) argued that changes in executive compensation are positively related to changes in current year stock price. Moreover, they argued that while the relation between changes in executive pay and changes in shareholder wealth is statistically significant (low correlation), much of the variance in executive compensation remains unexplained. The study conducted by Murphy (1985) is based on a sampling of 461 executives in 72 companies over 18 years, and the study conducted by Coughlan and Schmidt (1985) is based on a sampling of 249 executives from 249 companies over 4 years. However, Bickford (1981), Ellig (1984), Rich and Larson (1984), and Decktop (1987) argued that since stock prices are very sensitive to external events therefore may have little to do with how efficiently a firm is run and controlled by management. Jensen and Murphy (1990) finds that there is no correlation between CEO stock ownership and pay performance sensitivity, signifying that, typical 80 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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CEO rewards for corporate performance is from stock ownership rather than by cash incentives.
Overall, previous studies between CEO compensation, stock ownership, and stock price have not been researched on a frequent basis. The results range from nil to weak positive correlation between them. The sampling population is ranged from 72 to 249 companies. The period of study is ranged from four years to eighteen years. In addition, firm size has never been used as a control variable towards understanding the relationship between CEO cash compensation, stock ownership, and stock price, in clear terms.
2.4 CEO COMPENSATION AND FIRM SIZE 2.4.1 CEO Compensation and Firm Size Linkage Prasad (1974) believed that executive salaries appear to be far more closely correlated with the scale of operations than its profitability. He also believed that executive compensation is primarily a reward for previous sales performance and is not necessarily an incentive for future sales efforts. McEachern (1975) believed that executives are risk averse. They can reduce or eliminate risk exposure in their compensation package by decoupling their pay for performance and linking it to a more stable factor, firm size. Gomez-Mejia, Tosi and Hinkin (1987) believed that firm size is a 81 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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less risky basis for setting executives’ pay than performance, which was subject to many uncontrollable forces outside the managerial sphere of influence. Deckop (1988) believed that a strong sales compensation relationship would suggest that CEOs are given an incentive to maximize size rather than profitability. Tosi and Gomez-Mejia (1994) believed that measurement of firm size is the composite score of standardized values of reported total sales and number of employees. Gomez-Mejia and Barkema (1998) defined the relationship between CEO compensation and firm size as “positive”. That is, CEOs in large companies have a higher income than CEOs in small companies. This is supported by Finkelstein and Hambrick (1996), who believed that firm size is related to the level of executive compensation. This is further supported by Murphy (1985), who finds that holding the value of a firm constant, firm whose sales grow by 10% will increase CEO salary or bonus between 2% and 3% Therefore, it shows that size pay relation is causal, and CEOs can increase their pay by increasing firm size, even when increase in size reduces the firm’s market value. Shafer (1998) shown that pay sensitivity, which measured as change in CEO wealth per dollar and change in firm value, falls with the square root of firm size. That is, CEO incentives are 10 times higher for a $10 billion firm than for a $100 million firm.
The famous meta-analysis conducted by Tosi, Werner, Katz and Gomez-Mejia (2000), who finds that the estimated correlation between CEO pay and aggregate firm size factor is .643, signifying firm size account for over 40% of the variance in CEO pay. 82 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Similarly, the adjusted composite correlation between changes in CEO pay and changes in firm size is .225, accounting for about 5% of changes in CEO pay. As such, CEOs can exert more influence of firm size than performance when determining CEO compensation. This is supported by Sigler (2011), who stated that firm size appears to be the most significant factor in determining CEO compensation. His examination is based on 280 firms listed on the New York Stock Exchange from 2006 to 2009. This is further supported by Kostiuk (1990) and Posner (1987), who argued that the large firm size may be used to legitimize high CEO pay to rationalize the size premium, which includes greater organizational complexity and more human capital required to run the business. In addition, Gomez-Mejia (1994) believed that a host of structural factors and pragmatic problems make it difficult for corporations to effectively control executives, leading to compensation packages that are more closely tied to firm size than performance. On the other hand, Finkelstein and Hambrick (1989) finds in their study that the relationship between CEO compensation and firm size is ranged from nil to strong positive ratios. In addition, they find that total assets (proxy of firm size) are strongly related to CEO compensation. Conversely, Mehran (1995) and Eaton and Rosen (1983) find in their study that percentages of salary and bonus are inversely related to firm size. According to Tosi et al. (2000), most previous studies conducted between CEO compensation and firm size are remarkably inconsistent. This is supported by studies conducted by Belkaoui and Picur (1993), David, Koachhar, and Levitas (1998), and Gray and Cannella (1997), they find that correlation between firm 83 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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size and CEO pay are as low as .107, .110, and .170; however, studies conducted by Boyd (1994), Finkelstein and Boyd (1998), and Sanders and Carpenter (1998) find the correlations of .62, .50, and .42.
Overall, previous studies between CEO compensation and firm size have produced divergent results ranging from weak negative to strong positive ratios. These inconsistent findings may be due to the selection of different sample sizes, different measurement periods, and different proxies of firm size such as total sales, total number of employees, or total assets. In addition, firm size has never been used as a control variable towards understanding this relationship between the CEO cash compensation and firm size, in clear terms
2.5 CEO COMPENSATION AND CEO POWER 2.5.1 CEO Compensation and CEO Stock Ownership According to Jensen and Murphy (1990), voting power of CEO includes CEO and his immediate family stock ownership and the percentage of stocks over which CEO has a sale or shared power to direct the voting. It is believed that CEO’s in large firms tend to own less stock and have less compensation based incentives than CEOs in small firms. This is supported by Jensen and Murphy (1990), who finds that as a percentage of total corporate value, CEO stock ownership has never been high in large companies. That is, 84 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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there exists a small and insignificant positive coefficient of the ownership interaction variable, which implied that the relation between compensation and performance is independent of an executive’s stock holdings. In addition, according to their earlier (1989) study, they find that median CEO of one of nation’s 250 largest public companies own shares just over $2.4 million, less than 0.07% of the company’s market value. In addition, they find that 9 out of 10 CEOs own less than 1% of their company’s stock, and 1 in 20 CEOs own more than 5% of the company’s outstanding stocks. Overall, they find that CEOs receive about 50% of their base pay in the form of bonuses. Their study is based on sampling of 73 manufacturing firms during a 15 year period. This is supported by Cyert, Kang and Kumar (2002), who finds a negative correlation between large stockholders and CEO compensation. That is, doubling percentage ownership of external stakeholders reduces non salary compensation by 12% to14%. This is contradicted by an earlier study conducted by Mehran (1995), who finds a positive relationship between the percentage of total cash (salary and bonus) compensation and percentage of shares hold by managers. His study is based on one year’s collection of data. Ungson and Steers (1984) believed that firms where CEOs have large stock ownership and long tenure, they can largely shape their pay. Similarly, Finkelstein and Hambrick (1988) believed that the relative power of a CEO may affect the height of the hurdles that are set to qualify for contingent pay. In addition, they believed that strong family’s position in the firm will increase executive’s power. Moreover, they find that CEO compensation and CEO stock ownership are related in an inverted U-shaped 85 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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manner, compensation highest in situations where CEO stock ownership is characterized as moderate. That is, the point of inflection happened when CEO stock ownership reached about 9 percent in the first 18 years, beyond that, salaries started to decline due to tax preference of incurring capital gains over current income. Bertrand and Mullainathan (2000) finds that CEOs at firms lacking five percent (or larger) stock ownership tend to receive more luck based pay, that is, pay associated with profit increases that are entirely generated by external factors rather than by CEOs’ efforts. In addition, they also find that firms that have fewer external stakeholders, CEO cash compensation is marginally reduced when option based compensation is increased.
Overall, previous studies between CEO compensation and stock ownership have produced inconsistent results ranged from weak negative to good positive ratios. It is believed that these inconsistencies in the results are due to the selection of different sample sizes ranged from seventy three to two hundred and fifty companies; and the selection of a different study period ranged from one to fifteen years. The firm size has never been used as a control variable towards understanding the relationship between CEO compensation and stock ownership, in clear terms. 2.5.2 CEO Compensation and CEO Tenure Murphy (1986) stated that CEO performance is influenced by CEO tenure. That is, he believed that increased CEO tenure may promote principal trust of an agent and in turn 86 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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agent will take actions in the principal’s interest. Similarly, Sigler (2011) finds that CEO tenure appears to be an important variable in determining the level of CEO compensation. His examination is based on two hundred and eighty firms listed on the New York Stock Exchange from 2006 to 2009. In addition, Finkelstein and Hambrick (1989) believed that CEO tenure is thought to have a positive link with compensation. That is, pay steadily increases as CEO gains and solidify power over-time. However, they find in their study that such a relationship is not observed between CEO tenure and CEO pay. As such, they then decided to conduct additional testing, cross sectional associations of CEO compensation and CEO tenure, and have found that there is an existence of a curvilinear relationship, a U-shaped pattern. That is, CEO tenure increases pay up to 18 years and then it started to decline gradually. They have provided two possible explanations for this curvilinear relationship. Firstly, they believed that power accrues for a while and then diminishes due to CEO’s reduced mobility in the managerial labor market, or due to his evolution into a figurehead with one or two younger high priced executives carry the actual weight of a CEO’s job. Secondly, they believed that executives reached a point where they prefer stock over cash compensation. This could occur because of changes in family and financial circumstances. This supposition is supported when they have examined two sub samples and have found that stock compensation carries a higher proportion of total compensation. As such, they believed that CEO tenure increases a shift in pay mix from cash to stock earnings, support the notion that personal circumstances influence pay. In 87 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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addition, they believed that long CEO tenure will create opportunity to recruit sympathetic board members for CEOs. In addition, they find that the average tenure of a CEO is significantly lower in externally controlled firms (2.96 years) than management-controlled firms (5.92 years). Thus, they believed that the boards of externally controlled firms may not need to pay from profitability because CEO tenure is dependent on the owner’s satisfaction with CEO performance. Their study is based on a sample size of sixty companies. Pfeffer (1981) believed that the creation of a personal mystique which may induce unquestioned deference or loyalty, can be expected to occur when CEO power becomes institutionalized in the organization.
Overall, previous studies have shown that linear to curvilinear relationships existed between CEO compensation and CEO tenure. It is believed that these inconsistent results are due to the selection of different sample sizes ranged from sixty to two hundred and eighty companies; and selection of different study periods ranged from four to eighteen years. In addition, firm size has never been used as a control variable towards understanding the relationship between CEO compensation and CEO tenure, in clear terms. 2.5.3 CEO Compensation and CEO Age Deckop (1988) argued that CEO age has little effect on CEO compensation. However, Finkelstein and Hambrick (1989) finds an inverted U-shaped relationship between CEO 88 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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age and CEO cash compensation, indicating, CEO cash compensation increases until CEO reached the age of 59 years and then it starts to decline. This is consistent with the view that earnings over time is in line with CEO’s need for cash, which tends to drop off as he or she gets older due to no major expenditures to incur such as, house and child rearing expenses. This is supported by McKnight et al. (2000), who find that CEO compensation is positively related to a certain age, but it starts to decline afterward. This is further supported by Weir (2000), who finds that the relationship between CEO salaries and CEO age are significantly related but weakening over time, and the relationship between CEO age and CEO bonus appears nonlinear in nature. That is, at about age 53, the proportion of bonus as a percentage of salary begins to decrease at an increased rate. On the other hand, according to Gibbons and Murphy (1992), who finds that CEO age is a well-recognized determinant of compensation and have shown to be significantly related to CEO pay. Overall, previous studies have found the relationship between CEO compensation and CEO age as curvilinear. However, previous studies have lacked a detailed investigation of this relationship. In addition, firm size has never been used as a control variable towards a clear understanding of this relationship. 2.5.4 CEO Compensation and CEO Turnover Jensen and Murphy (1990) finds that CEO turnover probabilities are negatively and significantly related to changes in shareholder wealth. In addition, they concluded that 89 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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the dismissals were simply not an important source of CEO incentives. Gilson and Vetsuypens (1990) examined the nature of compensation packages for financially distressed firms. They found that within a small sample of financially distressed firms, when a turnover occurs, insider replacement CEOs were paid substantially less than their predecessors, but outsider replacement CEOs were paid substantially more. Similarly, Murphy and Oyer (2002) finds that outside CEO replacements receive higher compensation than inside CEO replacements. That is, outside replacement CEOs, at median, typically make $335,360 more than their predecessors while inside CEOs are typically paid only $126,156 more than their predecessors. Brickley (2003) concluded that firm performance continues to explain very little variation of CEO turnover. Overall, despite literature consisted of excellent theoretical discussions on this topic, yet it lacked consistent empirical studies on the relationship between CEO compensation and CEO turnover. Nevertheless, among available empirical studies, it was found that there was a positive relationship between CEO compensation and CEO turnover. However, previous studies have never used firm size as a control variable towards a clear understanding of the relationship between CEO cash compensation and CEO turnover. 2.5.5 CEO Compensation and 5% Management Ownership The study conducted by Boudreaux (1973), Plamer (1973), and Gomez-Mejia, Tosi, and Hinkin (1987) believed that when there is no external equity holder with at least five percent of the stock, firm is called management controlled firm. Jensen and Murphy 90 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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(1989) finds that executive inside stock ownership can provide incentives, but these holdings are not generally controlled by corporate board and the majority of top executives have small personal equity ownership. Mehran (1995) finds a negative relation between the management ownership and level of compensation. Core et al. (1999) finds that CEO equity ownership or the presence of another executive board member who owns at least 5% of the outstanding equity significantly reduces the level of CEO compensation. Bertrand and Mullainathan (2000) finds that CEOs in firms that lacks a five percent (or larger) external shareholder tend to receive more luck based pay, that is, pay associated with profit increases that are entirely generated by external factors rather than by managers’ efforts. In addition, they also find that firms lack large external shareholders, cash compensation of CEOs is less reduced when their option based compensation is increased. Overall, despite literature consisted of some excellent theoretical discussions on this topic, yet it lacked empirical studies between them. Nevertheless, among available empirical studies, it was found that there was a mixed relationship between CEO compensation and 5% management ownership. However, previous studies have never used firm size as a control variable towards a clear understanding between CEO cash compensation and 5% management ownership.
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2.5.6 CEO Compensation and 5% Individual/Institutional Ownership Gomez-Mejia, Tosi, and Hinkin (1987) finds that executives in externally controlled firms receive more compensation for performance and less for scale of operation than their counterparts in firms without dominant stockholders. In addition, they believed that outside dominant stockholders view firms primarily as investments and have power and incentive to align compensation of CEOs with performance of firms. Lambert et al. (1987) finds a negative relation between the existence of outside block holders that owns at least 5% of outstanding shares and executive compensation. This is supported by David, Kochar and Levitas (1998), who find that CEO pay is negatively correlated with the presence of pressure resistant institutional investors and positively correlated with presence of pressure sensitive ones. This is also supported by Cyert, Kang and Kumar (2002), who finds a negative relationship between equity ownership of largest shareholder and amount of CEO compensation. In addition, they find that doubling the percentage ownership of the outside shareholder reduces non salary compensation by 12-14%. This is further supported by Dyl (1998), who finds a negative relation between CEO equity ownership and compensation, which he blamed for monitoring activities that reduce agency costs. Overall, the literature has lacked empirical studies between CEO cash compensation and 5% individual/institutional ownership. Nevertheless, among available empirical studies, it was found that there was a negative relationship between CEO cash compensation and 5% individual/institutional ownership. However, previous 92 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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studies have never used firm size as a control variable towards clear understanding the relationship between CEO cash compensation and 5% management ownership.
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CHAPTER THREE METHODOLOGY AND METHODS
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CHAPTER 3 - METHODOLOGY AND METHODS 3.1 GENERAL DESCRIPTION This research is an empirical comparative study on the extent and nature of the relationship between CEO cash compensation, firm size, firm performance, and CEO Power, among TSX/S&P and NYSE indexes companies from 2005 to 2010. The aim and objective of this research is to understand the effect of firm sizes as a control variable on CEO cash compensation, and to understand CEO cash compensation systems of TSX/S&P and NYSE populations. This research will be an in-depth study, as it will use two sub variables for firm size, eight sub variables for firm performance, and seven sub variables for CEO power.
3.2 METHOD SELECTED Fielding and Fielding (1986, pp. 34) stated: “what is important is to choose at least one method which is specifically suited to explore structural aspects of the problem and at least one which can capture the essential elements of its meaning”. This research study requires collecting, counting, and classifying data, and performing analyses on statistical findings. It requires a process to include a method of deductive reasoning by the use of the measurement tools to collect the relevant data. In addition, it requires only establishing associations among variables using effect statistics such as 95 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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correlations. As such, quantitative research method will be selected for this research study. Bryman (1989) explained that quantitative research method tests hypotheses and identifies patterns in variables whereas qualitative method validates corporate information and informs some of methodological decisions. With its origins in the scientific empirical tradition, quantitative approach relies on numerical evidence to draw conclusions, to test hypotheses or theory, and is concerned with: measurement, causality, generalization, and replication. Burns (2000) believed that quantitative research method is infused with positivism and is based on a collection of quantifiable observations, which permits deduction of the laws and the establishment of relationships. In addition, Creswell (2009) stated that if problem calls for identification of factors that influence an outcome, the utility of an intervention, or understanding clear outcomes, then a quantitative approach is most suitable.
Within a quantitative research method framework, longitudinal survey method will be adopted to collect six years of data from 2005 to 2010. According to Zanaida and Fernando (2000), longitudinal design is seldom used in social science research; however, it is typically within financial investigations that have adopted positivist research philosophy. Buck et al. (2003) and McKnight and Tomkins (2004) believed that financial research is very typical for a positivist investigation. In addition, they believed that using a precise collection of data from annual reports are an obvious approach applied by researchers who have investigated chief executive pay in the past. This is 96 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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supported by Main & Johnson (1993), who believed that companies’ annual reports are a common resource tool when examining compensation details. Accordingly, this study will collect financial data of companies from highly credible SEDAR (represents United States Securities and Exchange Commission) and EDGAR (represents Canadian Securities Administrators) databases. The stratified sample method will be selected for this research study since it requires equal stratum and avoid selection bias towards determining sample sizes. That is, this research study will try to understand the effect of firm sizes on the relationship between CEO cash compensation, firm size, firm performance, and CEO power, among TSX/S&P and NYSE populations.
The surveys are believed to be useful when a researcher wants to collect data on phenomena that cannot be directly observed. It is a non-experimental, descriptive research method. Groves et al. (2004, pp. 4) stated: "survey is a systematic method for gathering information from (a sample of) entities for the purpose of constructing quantitative descriptors”. As such, this research study will use the survey method to collect data from 2005 to 2010. The linear regression method will be adopted in this research study to perform inferential statistical tests, that is, parametric and correlations to obtain, generalizability of the results. Gomez-Mejia and Balkin (1987), Finkelstein and Boyd (1998), and Gomez-Mejia, Tosi and Hinkin (2000) have used descriptive statistics and correlation approaches, to understand the relationship between CEO compensation and firm performance. In addition, Gupta, Kennedy and Weaver (2009) have also used 97 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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descriptive statistics in their study of the relationship between corporate governance and firm performance.
3.3 APPROPRIATENESS In quantitative research, data collection takes the form of measurements or counts which can be statistically analyzed. That is, quantitative research follows a process of standard procedures and methods, and standard form of analysis and reporting results, of research being undertaken. In addition, it is used to develop theories, identify and justify problems with current practices, and make judgments or identify what others in similar situations may be involved. Therefore, there is no manipulation of variables and no attempt is made to establish causality. In addition, it followed characteristics of objectivity, deductivism, replication, and generalizability. According to Duffy (1985,1986), in quantitative research, investigators maintained an objective view to understand facts, aimed to control or eliminate extraneous variables within the internal structure of the study, and data generated from research are used for standardized testing. The strength of such a detached approach is that it avoids researchers’ bias in the study and therefore ensuring objectivity. Thus, a quantitative approach is used as a vehicle for studying empirical world from the perspective of subject, not the researcher (Duffy, 1987). Cormack (1991) stated that quantitative research methodology tests deductive theory of existing knowledge through the development of hypothesized relationships and proposed outcomes. The process of measurement is central to 98 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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quantitative research because it provides a fundamental connection between empirical observation and mathematical expression of quantitative relationships. Blaikie (1993, pp.110) believed that positivism is the dominant philosophy of quantitative research and it is often used in natural sciences research. According to Denscombe (2003), positivism characteristic is archival research, which demands permanence of data to conduct studies. This is particularly relevant as it allows future researchers to replicate studies.
In contrary, the aim of qualitative research is to describe certain aspects of a phenomenon, with a view to explaining the subject of study (Cormack, 1991). Duffy (1985) described this concept as phenomenology, with its origins lying in the disciplines of history, philosophy, anthropology, sociology and psychology. Leach (1990) stated that phenomenology approach has no explicit intention to count or quantify findings, which are instead described in the language employed during the research process. Benoliel (1985) further elaborates qualitative research as modes of systematic inquiry concerned with understanding human beings and nature of their transactions. It offers insights and understandings of participants. It aims are to study subjects in their natural surroundings and to collect qualitative data. It described in words rather than numbers, and data are collected through observations and discussions. In addition, it includes structured and unstructured interviews, focus groups and ethnography studies.
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Furthermore, it highlights key themes or patterns emerge in projects, which are used to comprehend and manage data and test hypotheses.
Overall, this research study is primarily interested in finding the nature of the relationship than as to why the relationship exists, between CEO cash compensation, firm size, firm performance, and CEO power, among TSX/S&P and NYSE indexes companies. It is interested in empirical and factual than theoretical and exploratory information. It is interested in evidential and objectivity than circumstantial and subjectivity of sample data. It requires a large sample than a few case studies to address three research questions. It requires a collection of historical data than new exploratory data. In addition, it requires conducting structured questionnaire surveys than unstructured qualitative interviews or focus group studies. Therefore, quantitative research method will be adopted for this research.
3.4 RESEARCH DESIGN This research will follow the system of quantitative research framework. It will adopt a longitudinal study approach to collect six years of data from 2005 to 2010. The stratified sample method will be selected for this research study since it requires equal stratum and avoid selection bias towards determining sample sizes. That is, this research study will try to understand the effect of firm sizes on the relationship between CEO cash compensation, firm size, firm performance, and CEO power, among TSX/S&P and 100 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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NYSE populations. This research study will collect a total of two hundred and forty companies. Each population will have a total of one hundred and twenty companies. Each sub-population (small, medium, and large) will have a sample size of forty companies. The small size companies will be selected based on total revenues up to five hundred million dollars. The medium size companies will be selected based on total revenues over five hundred million to two billion dollars. The large size companies will be selected based on total revenues over two billion dollars. These specific ranges have been created to ensure maximum number of companies from diverse industry background will be available for a stratified sampling. The TSX/S&P sample population will be selected from Canadianbusiness.com website. The NYSE sample population will be selected from NYSE.com website. The survey method will be used to collect sample data. The historical data will be obtained from SEDAR and EDGAR databases. The survey form will consist of five sections, a total of fourteen questions. The SPSS and Microsoft Excel data sheets will be used for recording, processing, and presenting data. The data analysis will be based on the results obtained from descriptive statistics and panel regression such as, analysis of variance (ANOVA), chi-square, F-test, and t test. The scatter plots and histograms will be drawn to analyze the validity and extent of covariances and correlations among assigned variables. In the end, detailed step-by-step analysis will be performed, to address three research questions of this study. Following is the research design figure 1 titled: “Quantitative Research Design”
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FIGURE!4! Quantitative!Research!Design!
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3.5 VALIDITY AND RELIABILITY In the quantitative research method, researchers are always attempting to transform the subject into measurable or common categories to derive results. As a result, the data demands validity and reliability of research method and design, and statistics. That is, the construction of instruments and administration in the standardized manner based on predetermined procedures are primary requirement of quantitative research. Winter (2000, p. 287) stated that: “quantitative research limits itself to what can be measured or 102 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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quantified … within positivist terminology, and was the result and culmination of other empirical conceptions: universal laws, evidence, objectivity, truth, actuality, deduction, reason, fact, and mathematical data to name just a few”.
The validity determines whether research truly measures what it is intended to measure or how accurate research results. It consists of face validity, content validity, criterionrelated validity, construct validity, convergent validity, divergent validity, discriminant validity, statistical conclusion validity, and external validity. The face validity is concerned with how a measure or procedure appears. In this research, it will be based on designing a survey form to collect relevant data from companies for sampling. The content validity is concerned with the degree to which content of the test matches a content domain associated with the construct. In this research, it will be based on fourteen structured quantitative questionnaires on CEO cash compensation, firm size, firm performance, and CEO power. The criterion validity involves the correlation between test and criterion variables taken as representative of the construct. In this research, the criterion validity will be represented by firm performance, firm size, and CEO power. The construct validity will be based on a measure of how meaningful survey instruments or scale is used in practice. In this research, construct validity will be based on sub variables of all dependent and independent variables such as cash, bonus, net profit margin, return on assets, CEO total value of stocks, and 5% management ownership. There are two approaches to construct validity and they are 103 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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referred to as convergent validity and divergent validity. The convergent validity refers to the degree to which a measure correlates with other measures that is theoretically predicted to correlate with. Its validity is assessed by reviewing t-tests for factor loadings. If all t-tests have shown significant then they are effectively measuring same construct. In this research, t-tests will be conducted between sub variables of CEO cash compensation, firm performance, firm size, and CEO power. On the other hand, divergent validity describes the degree to which operationalization does not correlate with other operationalization, which theoretically should not correlate with. In this research, survey questions were not related and opposite to each other as such divergent validity is not applicable. The discriminant validity is demonstrated if variance extracted estimates are greater than squared correlation. This can be assessed through the results of linear regression - minimum and maximum values of sub variables. The statistical validity is the degree to which conclusions about the relationship among variables are correct. In this research study, statistical validity will be assessed based on linear regression test results with p-value (statistical significance) of .05. That is, pvalue must be less than .05 or 5% to reject the null hypothesis. The external validity is concerned with the extent to which the results of a study can be held true in other cases. In this research study, external validity will be based on analysis of variance and correlation results derived from thirty-six statistical models represent TSX/S&P and NYSE populations.
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The reliability of data is based on the assumption of reliability or repeatability. Primarily, it is concerned with whether the researcher obtains the same results if he could observe the same thing twice. The reliability consists of test-retest reliability, parallel form reliability, inter rater reliability, and internal consistency reliability. The test-retest reliability measures reliability over time. That is, to estimate reliability in repeated situations, observed scores will be calculated, and random and systematic error levels will be estimated and assigned. The lower the random and systematic errors, the higher will be the reliability of data. In this research, the use of historical data from corporate filings will create a high level of accuracy and consistency and thus will enhance reliability. The parallel forms reliability evaluates different questions and question sets that seek to assess same construct. It essentially evaluates two versions of forms by comparing their correlation coefficients. In this research, single survey form will be used for two hundred and forty companies as such, parallel forms reliability will not be applicable. Inter rater reliability evaluates reliability across different people. That is, how similar people categorize items and score items. This research will conduct structured questionnaire survey, as such inter rater reliability will not apply. The internal consistency reliability evaluates individual questions in comparison with one another for their ability to give consistently appropriate results. In this research all the questions and variables are independent of each other. As a result, Cronbach’s Alpha or Kuder Richardson coefficient test will not apply as internal consistency reliability.
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In addition, according to Hussey & Hussey (1997) and Remenyi et al. (1998), large sample size will enhance reliability and can increase population representation. McKnight (1996) and Conyon & Sadler (2001) stated that, as a result of poor response rates or as a deliberate methodological decision, previous studies had employed small sample sizes ranging from fifty to one hundred firms. As such, this research study will select a total sample size of two hundred and forty companies to achieve the reliability of the statistical results among TSX/S&P & NYSE populations.
3.6 SAMPLING METHOD The random sample is the purest form of probability sampling. Yates (2008, p. 27) believed that an unbiased random selection of individuals is important so that in the long run sample represents the population. However, this does not guarantee that a particular sample is a perfect representation by population. The random sample merely allows one to draw externally valid conclusions about the entire population. In addition, it is believed to be more difficult to identify every member of the population, so the pool of available subjects becomes biased. In contrast, the stratified sample method involves the division of a population into smaller groups known as strata. The researcher first identifies the relevant stratums and their actual representation in the population and then a random sample is used to select a sufficient number of subjects from each stratum. In addition, it minimizes the probability of an increase in sampling error. Yun and Teddlie (2007) states that if a researcher is interested in drawing a random sample, 106 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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then she or he typically wants sample to be representative of population on some characteristic of interest. The situation becomes more complicated when the researcher wants various subgroups in the sample to also be represented. In such cases, the researcher uses stratified random sampling, which combines stratified sampling with random sampling. Therefore, this research study will use stratified sampling method since it requires equally firm sizes (small, medium, and large) to validate comparisons of test results among TSX/S&P and NYSE populations.
3.7 DATA COLLECTION In this research, the data collection process starts with survey of two hundred and forty companies. The survey form will consist of five sections. The total of fourteen structured questions will be prepared to collect data on CEO cash compensation, firm size, firm performance, and CEO power. The financial data will be obtained from SEDAR (for TSX/S&P companies) and EDGAR (for NYSE companies) databases. The documents that will be examined are: annual report, audited annual financial statements, management information circular, and proxies and info statements. The survey form will use one and two digit coding to represent variables. The first section of survey form will be based on the background of a company - company name, stock exchange and industry the company represents, and total number of employees employed each year from 2005 to 2010. The second section of survey form will be based on firm performance, that is, total sales, return on total assets, return on equity, earnings per 107 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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share, cash flow per share, and net profit margin, for each year from 2005 to 2010. The third section of survey form will be based on remuneration, which is, CEO salary, CEO bonus, and CEO total compensation, for each year from 2005 to 2010. The fourth section of survey form will be based on CEO profile, that is, CEO age, CEO tenure, CEO turnover, CEO total stocks, and CEO total value of stocks, for each year from 2005 to 2010. The fifth section of survey form will be based on the firm’s ownership, that is, number of management individuals and individual/institutional investors owning at least 5% of the firm’s stock, CEO total common stocks, CEO total value of stocks, and total book and market values of common stocks in the company, for each year from 2005 to 2010.
The company will be classified as owner-managed or management-controlled based on individual/institutional or management individuals owning at least 5% of the company’s common stocks. Each group who owns at least 5% or greater will assign a value of “1”. The CEO age information will be counted backward from 2010 unless he left the company within this study period. The data on the market value of stock will be based on ending share price on Dec. 31 of each year from 2005 to 2010 Dec. 31. The stock prices for both TSX/S&P and NYSE companies will obtain from the TSX.com website. The financial ratios: return on total assets, return on equity, earnings per share, cash flow per share, net profit margin, book value per share, market value per share, and cash flow per share, will either directly obtain from the company’s annual audited report 108 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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or by performing manual calculation of accounts from the company’s balance sheets and income statements. The CEO remuneration: salary and bonus, will obtain from “proxies and info statements” or “management information circular” document. The CEO total cash compensation will be calculated based on CEO salary and CEO bonus. The CEO information: CEO tenure, number of years CEO is employed, CEO total stocks, and CEO total value of stocks, will obtain from proxies and info statements or management information circular document. The firm size: total sales and total number of employees employed, will obtain from the audited annual report.
Companies that do not file their financial information on a consistent (2005 to 2010) basis will not be included in the sample populations. That is, only those companies that are listed with TSX/S&P or NYSE index from 2005 to 2010 will be included in the sample population. This approach will be taken to obtain consistent and mature data from each company. Any survey question which cannot be answered from corporate records will be inquired from the company’s investor relations department. Once all two hundred and forty survey forms are completed, they will then be grouped according to total revenues. The total of six groups (small, medium, and large of TSX/S&P and NYSE populations) will be formed. Each group will consist of forty survey forms. All survey forms will be checked to ensure they are complete and accurate. The sample companies will be listed in Appendix B, and sample survey form will be illustrated in Appendix C. 109 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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In this research study, accounting ratios will represent firm performance, to understand the nature and extent of the correlations with CEO cash compensation. The accounting performance data are believed to be less affected by unpredictable market environment, and it provides performance information of management based on their activities. It will be based on earnings per share (EPS), return on equity (ROE), return on asset (ROA), cash flow per share (CFS), net profit margin (NPM), common stocks outstanding (CSO), the market value of common stocks outstanding (MVCSO), and book value of common stocks outstanding (BVCSO). Nyberg, Fulmer, Gerhart, and Carpenter (2010), Kerr and Bettis (1987), Deckop (1988), and Gomez-Mejia, Tosi, and Hinkin (1987), and many others have used these performance measures as a proxy for firm performance in their studies.
The data collection of CEO power will be based on: CEO age, CEO total stocks holdings, total value of CEO stocks, CEO tenure, CEO turnover, 5% management ownership, and 5% individual/institutional ownership. Gomez-Mejia, Tosi, and Hinkin (1987) believed that using 5% ownership convention, researchers have demonstrated significant differences between owner and management controlled firms on a variety of measures, including rates of return on investment (Boudreaux, 1973), risk aversion (Palmer, 1973), performance (Glassman and Rhoades, 1980, McEachern, 1975,
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Sorenson, 1971,1974), executive transitions (Salancik and Pfeffer, 1980), and antitrust activities (Blair and Kaserman, 1983, Chevalier, 1969).
The data collection of firm size will be based on total sales and total number of employees. Tosi and Gomez-Mejia (1994) have used total sales and total number of employees as proxies for firm size. The studies conducted by Eaton & Rosen (1983), Murphy (1985), Hill & Phan (1991), Krug (2003), and Datta et al. (2005), who have used the total number of employees as a standard and common measure for firm size.
3.8 DATA ANALYSIS Ostle and Malone (1988) believed that statistical analysis of data only described what is, and it cannot be determined what ought to be, except insofar as it may throw light upon probable concomitants and consequences of certain situations. In addition, they believed that data analysis is a tool used in designing research, analyzing data, and drawing conclusions. The data analysis for this research study will be based on two phases. The first phase of data analysis will be performed after the surveys are completed which includes checking for accuracy and completeness of survey forms; and data transformation from survey forms to Microsoft Excel spreadsheets and then to SPSS data sheets. The second phase of data analysis will consist of performing multivariate analysis in SPSS software. The multivariate analysis refers to statistical
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methods that simultaneously analyze multiple measurements on each variable under investigation. That is, a linear regression analysis will be conducted to analyze data.
During the first phase of data analysis, data will be transferred manually from survey forms to Microsoft Excel spreadsheets for electronically recording. In the Microsoft Excel spreadsheets columns and rows will be labeled according to variables. Each model data set will have separate sheets to ensure data are free from grouping error. Each data sheet will be checked to ensure all survey questions have been answered. It will be checked for accuracy by analyzing marginal variances from 2005 to 2010. It will be checked for outliers by observing and sorting data sheets by columns. Accordingly, if outliers are found then they will be cross-referenced to survey forms. On the data sheets, all companies will be checked by sorting “year” column, to ensure that they contain six years of information from 2005 to 2010. In addition, each data sheet will be formatted to four decimal places for financial ratios and zero decimal places for CEO compensation to achieve accuracy in the statistical results. The second phase of data analysis consisted of copying and pasting data from Microsoft Excel spreadsheets to SPSS data sheets. In SPSS, data sheets will be checked for accuracy and completeness by cross referencing to Microsoft Excel data sheets. The dependent and independent variables, regression coefficients, residuals, plots, predicted values, and distances will be analyzed from the linear regression test. The identified outliers from the linear regression test will be removed by deleting data 112 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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rows and conducting retest as required to achieve no outlets in the statistical model. The data will then be analyzed in nine steps. The first step will consist of an analysis of mean and standard deviation of each variable. The second step of data analysis will consist of a Pearson correlation test and test of significance. The third step of data analysis will consist of regression (R2) and change statistics tests. The fourth step of analysis will consist of analysis of variance (ANOVA) test, F-test, residual test, and pvalue or confidence interval test. The fifth step of data analysis will consist of unstandardized and standardized coefficient tests, t-test, and collinearity statistics test. The sixth step of data analysis will consist of correlations and covariance tests. The seventh step of the data analysis will consist of eigenvalue, condition index, and variance proportion tests. The eighth step of data analysis will consist of a predicted value, standard predicted value, Cook’s distance, and Mahal distance tests. The ninth and final step of data analysis will consist of graphs: histogram, regression standardized residual, scatter plot, and partial regression residual plot tests. According to Glenberg and Langston (1992), descriptive results are graphical representation of associations among variables as such it easier to identify relations among data. Glenberg and Langston (1992) stated that inferential statistics find correlations or relationships among variables as such has led to greater comprehension of data. According to Holland (1986), correlation did not imply causation. This is also highlighted by Pavlik et al. (1993) who argued that most studies relied on ex-post correlations and one cannot infer causation from them. Also, most variables that are expected to influence executive pay 113 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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tended to be highly correlated and this posed a collinearity problem that makes it difficult to isolate unique effects of any single factor (Gomez-Mejia, 1994). Hinton (1995) stated that ANOVA analysis is an appropriate statistical test when correlating more than two variables. According to Lewis-Beck (1993), multiple regressions are an extension of bivariate regression and are used for prediction as well as an explanation. It offers a fuller explanation of dependent variable since few phenomena are products of a single cause. In addition, it ensures that the effect of a particular independent variable is made more certain for the possibility of distorting influences from other independent variables if it were removed. That is, multiple regressions hold constant other independent variables through statistical control as opposed to experimental control. According to Fattorusso (2006), due to a wide variety of internal and external contingencies surrounding executive bonuses, it is worth acknowledging that direction of causation with regard to bonus pay and firm performance is, if at all, difficult to determine. Therefore, the results were discussed in terms of associations rather than causations. The use of the panel regression analysis technique will enable to understand the nature and extent of relationships between dependent and independent variables. Hsiao (2003) stated that panel regression analysis will provide more data points, thereby, will increase the degrees of freedom and reduce collinearity among explanatory variables, which will create efficiency of econometric estimates.
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3.9 SUMMARY This research study is an empirical study which requires the use of descriptive statistics and correlations to understand the extent and nature of the relationship between CEO cash compensation, firm size, firm performance, and CEO power, among TSX/S&P and NYSE indexes companies. As a result, it demands objectivity, preciseness, and numerical results. It requires extraction of historical data from companies’ corporate records and fillings. It requires verification of data and assigning variables in the statistical model, to achieve precise results and objective interpretations. It requires the adoption of positivist and deductive approaches. Hence, quantitative research method will be selected for this research study. On the other hand, this research will not select a qualitative research method due to its emphasis on phenomenological approaches rather than positivist approaches. It uses inductive and holistic approaches rather than deductive and particular approaches. It is subjective-centered and process-oriented rather than objective-centered and outcome-oriented. And it is designed to be exploratory rather than confirmatory.
The longitudinal study method will be selected to collect six years of data from 2005 to 2010. The stratified sampling method will be selected to understand the effect of firm size as a control variable on the relationship between CEO cash compensation, firm size, firm performance, and CEO power, and to form a proper comparative analysis of 115 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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TSX/S&P and NYSE compensation systems. This research will have a total sample size of two hundred and forty companies from TSX/S&P and NYSE populations. The TSX/S&P sample population will be selected from the CanadianBusiness.com website. The NYSE sample population will be selected from the NYSE.com website. Each population will have a sample population of one hundred and twenty companies. The three sub-populations of small, medium, and large will be created to represent firm sizes. Each sub-population will consist of forty companies.
The survey method will be adopted to conduct surveys. A survey form will consist of five sections comprise of background of company, firm performance, remuneration, CEO profile, and firm’s ownership. The totaled of fourteen structured questionnaires will be developed to obtain data on CEO cash compensation, firm size, firm performance, and CEO power. The SEDAR and EDGAR databases will be used to obtain financial data. The documents to be examined consist of the proxies and info statements, annual report, audited annual financial statements, and management information circular. Each completed survey form will be checked for accuracy and completeness. The outliers will be investigated by cross-referenced to survey forms. Once all survey forms are completed, they will be manually recorded into Microsoft Excel spreadsheets. The data will then be checked for input errors, outliers, and unformatted cells, before they are copied and pasted to SPSS software data sheet. In SPSS software, separate files will be created and saved for each model test. The linear regression analysis will be 116 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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performed to understand the relationship between CEO cash compensation, firm size, firm performance, and CEO power. In the linear regression analysis, all columns will be labeled and will accordingly assign as dependent or independent variable. The regression coefficients, residuals, plots, predicted values, distances, and ninety five percent confidence interval limits will be selected to conduct the linear regression test. Each model test results will be saved separately in SPSS database. They will then be transferred to Microsoft Excel spreadsheets for formatting before they will be copied and pasted in Appendix D for presentation. In the end, conclusions will be drawn based on data results. 3.9.1 Description of Data The data presentation will be based on collecting, processing, analyzing, and interpreting results. That is, it includes tabulation, diagrammatic representation, and descriptive methods. It will explain what have discovered from data testing, what changes happened as a result of data findings, and what conclusions drawn from statistical findings. Each section will discuss on analysis of variance (ANOVA) results to address model fitness, Pearson correlations results to address relations among predictor variables, p-value analysis to address model significance, model coefficients and variables results to address the extent and nature of influence of betas and predictors; t-tests results to address means of normal distributions; collinearity tests results (tolerance level and variance inflation factor) to address model validity and 117 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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addressing multi-collinearity concern; model linearity test result from normal probability plot of regression to address normality of model; hetroscedasticity and homoscedasticity tests results from graphical methods to address variance of residuals; and concluding by either accepting or rejecting null hypothesis statement. The comprehensive statistical results of each model will be presented in Appendix D. And the detailed scientific data analyses will be provided in Chapter 4.
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CHAPTER FOUR DATA PRESENTATION
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CHAPTER FOUR - DATA PRESENTATION 4.1 PURPOSE OF DISSERTATION The purpose of this research is to investigate in clear terms the extent and nature of the relationship between CEO cash compensation, firm size, firm performance, and CEO power, among TSX/S&P and NYSE indexes companies from 2005 to 2010. To understand TSX/S&P and NYSE populations CEO cash compensation systems. To clarify shareholders, investors, and the public on determinants of CEO cash compensation, that is, compensation factors that involved in rewarding CEOs with salaries and bonuses.
4.2 RESEARCH METHOD This research requires collecting, counting, and classifying data, and performing analyses on statistical findings. It requires a process to include method of deductive reasoning by the use of measurement tools to collect relevant data. It requires only establishing associations among variables using effect statistics such as correlations. It requires studying historical data, testing hypotheses, conducting questionnaire surveys, adopting the method of deductive reasoning by the use of measurement tools to collect data, predicting causal relationships, and numerical calculations to obtain objective results and drawing clear conclusions. As such, the quantitative research method is 120 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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selected for this research study. The longitudinal study method is selected to collect data for the six year period from 2005 to 2010. The stratified sampling method is selected to obtain equal sample sizes for small, medium, and large companies. The survey method is selected to collect financial data using structured questionnaire approach. The inferential statistical methods such as parametric and correlations will be used to achieve generalizability of the results. That is, linear regression analysis is selected to understand the relationship between CEO cash compensation, firm size, firm performance, and CEO power, among TSX/S&P and NYSE indexes companies.
4.3 DATA COLLECTION In this research, the data collection process started with survey of two hundred and forty companies. The survey form had consisted of five sections: background, firm performance, remuneration, CEO profile, and firm’s ownership. The total of fourteen structured questions was created to collect data on CEO cash compensation, firm size, firm performance, and CEO power. The financial data were obtained from SEDAR (for TSX/S&P companies) and EDGAR (for NYSE companies) databases. The documents that were examined include annual report, audited annual financial statements, management information circular, and proxies and info statements. The survey form had used one and two digits coding to represent variables. The financial ratios were calculated from the company’s balance sheets and income statements to obtain company’s performance data. The data on market value of stock will be based on 121 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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ending share price on Dec. 31 of each year from 2005 to 2010 Dec. 31. The year ended stock price for both TSX/S&P and NYSE companies were obtained from the TSX.com website. The companies that didn’t file their financial information on a consistent (2005 to 2010) basis had not been included in sampling population. That is, those companies that no longer associated with TSX/S&P or NYSE index from 2005 to 2010 had been excluded from sample population. This approach was taken to obtain consistent and mature data from each company. Any survey question which could not be answered from corporate records was inquired from the company’s investor relations department. Once data were collected, survey forms were grouped into small, medium, and large based on total revenues.
During the data collection process, it was found that some company’s stock prices on Dec. 31, 2005 and Dec. 31, 2006 weren’t available on TSX.com website, and CEO age information was not provided for most of Canadian companies. Due to this, the investor relations department of concerned companies were contacted by email to obtain information. In addition, information relating to 5% management stock ownership and 5% individual/institutional stock ownership were found challenging. That is, it demanded a detailed examination of “management and info circular” document of TSX/S&P companies and “proxies and info statements” document of NYSE companies.
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4.4 DATA DISTILLATION The data were analyzed based on small, medium, large, and total population. The company size was assigned based on total revenues. Each data group consisted of two hundred and forty observations (forty companies' times six years), except for total group which consisted of seven hundred and twenty observations (one hundred and twenty companies' times six years). Within those six data groups thirty-six subgroups was formed based on TSX/S&P and NYSE populations, CEO cash compensation, firm size, firm performance, and CEO power. For example: TSX/S&P, small size company, and CEO salary; or NYSE, small size company, and CEO salary. The purpose of forming thirty-six sub data groups was to answer three research questions of this study. At the end of surveys, data were first analyzed for accuracy and completeness. If the surveys were found to have errors then they were cross-referenced to corporate filings to verify and perform corrections. In addition, data were checked for proper formatting such as requirement of four decimal places for financial ratios, no decimal places for CEO compensation, and no symbol and punctuation mark in each data cell. Thirty-six Microsoft Excel spreadsheets were created and named based on population, firm size, and CEO compensation, to represent each subgroup of data. In the Microsoft Excel spreadsheet, columns of data were labeled with sub variables of dependent and independent variables, and rows were labeled with company names, to ensure all data were correctly represented. The data were then sorted based on company name and 123 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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year, to ensure each company had consisted of six years of data. Multiple files were created and saved to protect against data corruption or a virus attack. In addition, they were stored on a USB hard drive, in the event that files became corrupted. Once data were formatted in Microsoft Excel spreadsheets, they were re-checked for accuracy and completeness. The final step in Microsoft Excel was to copy and paste each spreadsheet data to SPSS “data view” tab. Each SPSS data file was then formatted and labeled in the “variable view” tab which consisted of name, type, width, decimals, label, value, missing column, align, measure, and role. Accordingly, thirty-six separate files were created, named, and saved in the SPSS database before they were tested. The linear regression analysis dialogue box was opened. It consisted of dependent and independent variables, regression coefficients (estimates, 95% confidence intervals, covariance matrix, model fit and R-squared change, descriptive, part and partial correlation, and collinearity diagnostics), residuals (Durbin-Watson and caseware diagnostic), linear regression plots (histogram and normal probability plot), predicted value and residuals (unstandardized and standardized), distances (Cook’s), and prediction intervals (mean and individual), were selected for testing. Once these features were selected, accordingly linear regression tests were conducted. The most important test result to observe was “caseware diagnostic”. This test revealed outliers that required to be deleted. As such, the testing process was repeated until no outlier was reported in model test results. Some models were tested up to fifteen times to
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eliminate outliers. This process had ensured data were highly distilled to get accurate results.
4.5 DATA FINDINGS 4.5.1 Null Hypothesis Testing Among TSX/S&P and NYSE populations, a total of thirty-six models were tested using the linear regression method in SPSS software. That is, thirty-six operational null hypotheses were tested using combinations of sub dependent and sub independent variables. The first research question was: among TSX/S&P and NYSE indexes companies, what relationship is there between CEO cash compensation and firm size?. The second research question was: among TSX/S&P and NYSE indexes companies, what relationship is there between CEO cash compensation and firm performance?. The third research question was: among TSX/S&P and NYSE companies, what relationship is there between CEO cash compensation and CEO power?. 4.5.1.1 Operational Hypothesis Statement 1 H0 :
Among TSX/S&P and NYSE indexes companies, there is no relationship between CEO cash compensation (salary and bonus) and firm size (return on sales and total number of employees).
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H1 :
Among TSX/S&P and NYSE indexes companies, there is a relationship between CEO cash compensation (salary and bonus) and firm size (return on sales and total number of employees).
For operational hypothesis statement 1, separate models were developed for each dependent variable:
Salary: Y1=c+B1X1+B2X2+ Bonus: Y2=c+B1X1+B2X2+
Y1=salary; Y2=bonus; c=constant predictor; B1=influential factor for sales; B2=influential factor for total number of employees; X1=value of total Sales; X2= value of total employees; and
=error.
The confidence level (α) was set at 5 percent for one-tailed test. df=degree of freedom
weak ratio=+/- .000 to .249; moderate ratio=+/- .250 to .499; good ratio=+/- .500 to .749 strong ratio=+/- .750 to 1.000.
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4.5.1.2 CEO Cash Compensation vs. Firm Size (TSX/S&P & NYSE Small, Medium, And Large Populations) The purpose of this section was to understand the nature and extent of the relationship between CEO cash compensation and firm size. The twelve statistical models were tested based on firm sizes of small, medium, and large from TSX/S&P and NYSE indexes. Each statistical model consisted of forty companies. The comprehensive results were provided in Appendix D section 1.1 to 1.12 for review. Analysis of variance (ANOVA): The following table summarized ANOVA findings between CEO salary, CEO bonus, and firm size of TSX/S&P index companies:
Table 4.5.1.2A ANOVA (TSX/S&P – CEO cash compensation vs. firm size) Small Medium Large F(2,236)=83.784 F(2,231)=34.309 F(2,236)=25.510 Salary vs. p=.000 p=.000 p=.000 firm size 2 2 R =0.145 R =0.229 R2=0.182 F(2,216)=15.948 F(2,226)=7.919 F(2,212)=12.863 Bonus vs. p=.000 p=.000 p=.000 firm size R2=0.129 R2=0.065 R2=0.106
The results had indicated that there were relationships between CEO salary, CEO bonus, and firm size among all six models as such, operational null hypotheses were rejected at α=.05. The regression (R2) was found to be ranged from weak to moderate 127 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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ratios across all six firm sizes. The following table summarized findings between CEO salary, CEO bonus, and firm size of NYSE index companies.
Table 4.5.1.2B ANOVA (NYSE – CEO cash compensation vs. firm size) Small Medium Large F(2,235)=84.103 F(2,233)=10.340 F(2,229)=36.659 Salary vs. p=.000 p=.000 p=.000 firm size R2=0.412 R2=0.286 R2=0.243 F(2,215)=15.502 F(2,231)=1.759 F(2,218)=5.558 Bonus vs. p=.000 p=.175 p=.004 firm size 2 2 R =0.126 R =0.015 R2=0.049
The results had indicated that there were relationships between CEO salary, CEO bonus, and firm size, except for the relationship between CEO bonus and firm size in the medium sized company as such, five operational null hypotheses were rejected at α=.05. The regression (R2) was found to be ranged from weak to moderate ratios across all six firm sizes.
Correlations: In TSX/S&P small population, correlation results had shown a good positive correlation of 0.574 between salary and total sales; and good positive correlation of .54 between salary and total employees. The moderate positive correlation of 0.358 between bonus and total sales; and weak positive correlation of .125 between bonus and total employees. In NYSE small population, correlation results had shown a good positive 128 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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correlation of 0.575 between salary and total sales; and good positive correlation of .542 between salary and total employees. The moderate positive correlation of 0.353 between bonus and total sales; and weak positive correlation of .121 between bonus and total employees.
In TSX/S&P medium population, correlation results had shown a moderate positive correlation of 0.477 between salary and total sales; and weak positive correlation of .029 between salary and total employees. The moderate positive correlation of 0.25 between bonus and total sales; and weak negative correlation of -.019 between bonus and total employees. In NYSE medium population, correlation results had shown a weak positive correlation of 0.107 between salary and total sales; and weak negative correlation of -.208 between salary and total employees. The weak positive correlation of 0.121 between bonus and total sales; and also weak positive correlation of .027 between bonus and total employees.
In TSX/S&P large population, correlation results had shown a good positive correlation of 0.279 between salary and total sales; and good positive correlation of -.083 between salary and total employees. The moderate positive correlation of 0.32 between bonus and total sales; and weak positive correlation of .112 between bonus and total employees. In NYSE large population, correlation results had shown a moderate positive correlation of 0.422 between salary and total sales; and also 129 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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moderate positive correlation of .407 between salary and total employees. The good positive correlation of 0.09 between bonus and total sales; and good positive correlation of .15 between bonus and total employees.
T-tests: In TSX/S&P & NYSE small populations, t-tests between salary, bonus, total sales, and total number of employees had resulted in rejecting the null hypothesis, indicated variable means were different. However, t-tests between bonus and total number of employees had resulted in accepting the null hypothesis, indicated variable means were same. In TSX/S&P and NYSE medium populations, t-tests between salary, bonus, total sales, and total number of employees had resulted in rejecting the null hypothesis, indicated variable means were different. However, in TSX/S&P medium population, ttests between salary, bonus, and total number of employees had resulted in accepting the null hypothesis, indicated variable means were same. In TSX/S&P and NYSE large population, t-tests between salary, bonus, total sales, and total number of employees had resulted in rejecting the null hypothesis, indicated variable means were different. However, in TSX/S&P large population, t-tests between bonus and total number of employees had resulted in accepting the null hypothesis, indicated variable means were same.
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Collinearity diagnostics: The collinearity test assessed the extent of correlation between independent variables. It was based on a tolerance level7, variance inflation factor (VIF)8, eigenvalues9, and condition index10. The twelve statistical model test results had indicated that they were within defined respective relevant ranges, as mentioned in footnotes. As such, multicollinearity11 was not a concern in all twelve models.
Model validity: A valid model requires a variance of residuals that are homogeneous across predicted values, known as homoscedasticity. If a model is well fitted, there should be no pattern to residuals plotted against fitted values. If the variance of residuals is non-constant then residual variance is said to be heteroscedastic. In this research, graphical methods (histogram and scatter plots) were used to detect heteroscedasticity between salary, bonus, total sales, and total number of employees, among TSX/S&P and NYSE small, medium, large, and total populations. It was found from these graphical results that there wasn’t any concern of existence of hetroscedasticity as such, all twelve models were described as homoscedastic. 7 Tolerance level should be within .95 or 95% confidence interval limit. 8 It measures severity of multicollinearity in regression analysis. It should be less than 5 to avoid concerns of multicollinearity. 9 Eigenvalues close to zero indicate a multicollinearity problem. 10 If condition index is 15, multicollinearity is a concern, and if it is greater than 30, multicollinearity is a very serious concern. 11 When a regressor is nearly a linear combination of other regressors in the model, affected estimates are unstable, and have high standard errors.
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Model linearity: A linear regression test assumes that the relationship between response and predictor variables is linear. It is conducted by drawing a straight line on data points. In this research, linearity assumption was assessed from the normal probability plot of regression-standardized residual. It was found that in all twelve statistical results, expected and observed probabilities were not divergent to the extent of showing curved band or a big wave shaped curve as such, relationships between salary, bonus, total compensation, total sales, and total number of employees, among TSX/S&P and NYSE small, medium, large, and total populations were close to linear. In addition, histograms had shown normal distributions. 4.5.2 Operational Hypothesis Statement 2 H0 :
Among TSX/S&P and NYSE indexes companies, there is no relationship between CEO cash compensation (salary and bonus) and firm performance (return on assets, return on equity, earnings per share, cash flow per share, net profit margin, common stocks outstanding, book value of common stocks outstanding, and market value of common stocks outstanding).
H1 :
Among TSX/S&P and NYSE indexes companies, there is a relationship between CEO cash compensation (salary and bonus) and firm performance (return on assets, return on equity, earnings per share, cash flow per share, net profit 132 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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margin, common stocks outstanding, book value of common stocks outstanding, and market value common stocks outstanding).
For Operational Hypothesis Statement 2, separate models were developed for each dependent variable:
Salary:
Y1=c+ B1X1+B2X2+B3X3+B4X4+B5X5+B6X6+B7X7+B8X8 +
Bonus:
Y2=c+ B1X1+B2X2+B3X3+B4X4+B5X5+B6X6+B7X7+B8X8+
(Y1=salary; Y2=bonus; c=constant predictor; B1=influential factor for return on assets; B2=influential factor for return on equity; B3=influential factor for earnings per share; B4=influential factor for cash flow per share; B5=influential factor for net profit margin; B6=influential factor for common stocks outstanding; B7=influential factor for book value per common stocks outstanding; B8=influential factor for market value per common stock outstanding; and
=error)
Let X1=value of return on assets; X2=value of return on equity; X3=value of earnings per share; X4=value of common stocks outstanding; X5=value of net profit margin; X6=value of common stocks outstanding; X7=value of the book value of common stocks outstanding; B8=value of the market value of common stocks outstanding. 133 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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The confidence level (α) was set at 5 percent. df=degree of freedom Weak ratio=+/- .000 to .249; moderate ratio=+/- .250 to .499; good ratio=+/- .500 to .749 strong ratio=+/- .750 to 1.000. 4.5.2.1 CEO Cash Compensation vs. Firm Performance (TSX/S&P & NYSE Small, Medium, and Large Populations) The purpose of this section was to understand the nature and extent of the relationship between CEO cash compensation and firm performance. The twelve statistical models were tested based on firm sizes of small, medium, and large from TSX/S&P and NYSE indexes. Each statistical model consisted of forty companies. The comprehensive results were provided in Appendix D section 2.1 to 2.12 for review.
Analysis of variance (ANOVA):
Table 4.5.2.1A TSX/S&P (CEO cash compensation vs. Firm performance) Small Medium Large Salary vs. F(8,230)=26.814 F(8,224)=4.524 F(2,224)=8.387 Firm p=.000 p=.000 p=.000 2 2 2 performance R =0.139 R =0.230 R =0.483 Bonus vs. F(8,212)=52.923 F(8,217)=2.711 F(2,218)=14.21 Firm p=.000 p=.000 p=.000 2 2 performance R =0.666 R =0.091 R2=0.350
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The results had indicated there were relationships between CEO salary, CEO bonus, and firm performance among all six models as such, operational null hypotheses were rejected at α=.05. The regression (R2) was found to be ranged from weak to moderate ratios across all eight firm sizes. The following table had summarized ANOVA findings between CEO salary, CEO bonus, and firm performance of NYSE index companies:
Table 4.5.2.1B NYSE (CEO cash compensation vs. Firm performance) Small Medium Large Salary vs. Firm performance Bonus vs. Firm performance
F(8,230)=7.045 p=.000 R2=0.197 F(8,225)=8.058 p=.000 R2=0.223
F(2,228)=2.474 p=.014 R2=0.08 F(2,225)=5.89 p=.000 R2=0.173
F(2,228)=13.669 p=.000 R2=0.306 F(2,212)=2.689 p=.008 R2=0.092
The results had indicated there were relationships between CEO salary, CEO bonus, and firm performance among all six models as such, operational null hypotheses were rejected at α=.05. The regression (R2) was found to be ranged from weak to moderate ratios across all six firm sizes.
Correlations: In TSX/S&P small population, correlation results had shown a good positive correlation of 0.74 between salary and return on assets (ROA); a weak positive correlation of .136 between salary and return on equity (ROE); a weak positive correlation of .036 between 135 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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salary and earnings per share (EPS); a weak negative correlation of -.02 between salary and cash flow per share (CFPS); a weak positive correlation of .077 between salary and net profit margin (NPM); a moderate positive correlation of .421 between salary and common stocks outstanding (CSO); a good positive correlation of .601 between salary and book value per share outstanding (BVCSO); and a good positive correlation of .627 between salary and market value per share (MVCSO). In addition, it was found that correlation between NPM and MVCSO was .208 which indicated that both variables had similar levels (weak positive ratios) of influence to salary model.
In TSX/S&P small population, correlation results had shown a weak positive correlation of 0.148 between bonus and return on assets (ROA); a weak positive correlation of .134 between bonus and return on equity (ROE); a weak positive correlation of .008 between bonus and earnings per share (EPS); a weak negative correlation of -.053 between bonus and cash flow per share (CFPS); a weak positive correlation of .111 between bonus and net profit margin (NPM); a moderate positive correlation of .491 between bonus and common stocks outstanding (CSO); a good positive correlation of .718 between bonus and book value of common stocks outstanding (BVCSO); and a good positive correlation of .663 between bonus and market value of common stocks outstanding (MVCSO). In addition, it was found that correlation between NPM and MVCSO was .192 which indicated that both variables had different levels (weak positive and good positive ratios) of influence to bonus model. 136 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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In NYSE small population, correlation results had shown a weak positive correlation of 0.068 between salary and return on assets (ROA); a good positive correlation of .148 between salary and return on equity (ROE); a good negative correlation of -.52 between salary and earnings per share (EPS); a good positive correlation of .50 between salary and cash flow per share (CFPS); a weak negative correlation of -.173 between salary and net profit margin (NPM); a weak positive correlation of .085 between salary and common stocks outstanding (CSO); a weak positive correlation of .243 between salary and book value of common stocks outstanding (BVCSO); and a weak positive correlation of .148 between salary and market value of common stocks outstanding (MVCSO). In addition, it was found that correlation between NPM and MVCSO was .590 which had indicated that both variables had similar levels (weak positive ratios) of influence to salary model. In NYSE small population, correlation results had shown a weak positive correlation of 0.039 between bonus and return on assets (ROA); a weak negative correlation of -.051 between bonus and return on equity (ROE); a weak positive correlation of .05 between bonus and earnings per share (EPS); a weak negative correlation of -.066 between bonus and cash flow per share (CFPS); a weak positive correlation of .076 between bonus and net profit margin (NPM); a weak positive correlation of .045 between bonus and common stocks outstanding (CSO); a moderate positive correlation of .407 between bonus and book value of common stocks outstanding (BVCSO); and a weak negative correlation of -.02 between bonus and market value of common stocks outstanding (MVCSO). 137 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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In TSX/S&P medium population, correlation results had shown a weak positive correlation of 0.01 between salary and return on assets (ROA); a weak positive correlation of .039 between salary and return on equity (ROE); a weak negative correlation of -.005 between salary and earnings per share (EPS); a weak positive correlation of .028 between salary and cash flow per share (CFPS); a weak positive correlation of .182 between salary and net profit margin (NPM); a moderate positive correlation of .294 between salary and common stocks outstanding (CSO); a moderate positive correlation of .330 between salary and book value of common stocks outstanding (BVCSO); and a moderate positive correlation of .310 between salary and market value of common stocks outstanding (MVCSO). In addition, it was found that correlation between NPM and MVCSO was .250 which indicated that both variables had similar levels (moderate positive ratios) of influence to salary model.
In TSX/S&P medium population, correlation results had shown a weak positive correlation of 0.12 between bonus and return on assets (ROA); a weak negative correlation of .075 between bonus and return on equity (ROE); a weak positive correlation of .054 between bonus and earnings per share (EPS); a weak negative correlation of -.002 between bonus and cash flow per share (CFPS); a weak positive correlation of .142 between bonus and net profit margin (NPM); a weak positive correlation of .240 between bonus and common stocks outstanding (CSO); a moderate positive correlation of .270 between bonus and book value of common stocks 138 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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outstanding (BVCSO); and a weak positive correlation of .211 between bonus and market value of common stocks outstanding (MVCSO).
In NYSE medium population, correlation results had shown a weak positive correlation of 0.005 between salary and return on assets (ROA); a weak positive correlation of .015 between salary and return on equity (ROE); a weak negative correlation of .103 between salary and earnings per share (EPS); a weak positive correlation of .142 between salary and cash flow per share (CFPS); a weak positive correlation of .118 between salary and net profit margin (NPM); a moderate positive correlation of .192 between salary and common stocks outstanding (CSO); a moderate positive correlation of .04 between salary and book value of common stocks outstanding (BVCSO); and a moderate positive correlation of .194 between salary and market value of common stocks outstanding (MVCSO).
In NYSE medium population, correlation results had shown a weak positive correlation of 0.117 between bonus and return on assets (ROA); a weak negative correlation of .065 between bonus and return on equity (ROE); a weak negative correlation of -.008 between bonus and earnings per share (EPS); a weak positive correlation of .029 between bonus and cash flow per share (CFPS); a weak positive correlation of .230 between bonus and net profit margin (NPM); a weak positive correlation of .180 between bonus and common stocks outstanding (CSO); a weak positive correlation of 139 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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.129 between bonus and book value of common stocks outstanding (BVCSO); and a weak positive correlation of .015 between bonus and market value of common stocks outstanding (MVCSO).
In TSX/S&P large population, correlation results had shown a weak positive correlation of 0.025 between salary and return on assets (ROA); a weak positive correlation of .186 between salary and return on equity (ROE); a weak negative correlation of -.100 between salary and earnings per share (EPS); a weak negative correlation of -.008 between salary and cash flow per share (CFPS); a moderate positive correlation of .427 between salary and net profit margin (NPM); a moderate positive correlation of .267 between salary and common stocks outstanding (CSO); a moderate positive correlation of .283 between salary and book value of common stocks outstanding (BVCSO); and a moderate positive correlation of .263 between salary and market value of common stocks outstanding (MVCSO). In addition, it was found that correlation between NPM and MVCSO was .534 which indicated that both variables had the same levels (weak positive ratios) of influence to salary model.
In TSX/S&P large population, correlation results had shown a weak positive correlation of -0.11 between bonus and return on assets (ROA); a weak negative correlation of .13 between bonus and return on equity (ROE); a weak negative correlation of .057 between bonus and earnings per share (EPS); a weak positive correlation of -.15 140 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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between bonus and cash flow per share (CFPS); a weak positive correlation of .527 between bonus and net profit margin (NPM); a weak positive correlation of .336 between bonus and common shares outstanding (CSO); a weak positive correlation of .425 between bonus and book value of common stocks outstanding (BVCSO); and a weak positive correlation of .34 between bonus and market value of common stocks outstanding (MVCSO).
In NYSE large population, correlation results had shown a weak positive correlation of 0.108 between salary and return on assets (ROA); a weak positive correlation of .012 between salary and return on equity (ROE); a weak negative correlation of .207 between salary and earnings per share (EPS); a weak positive correlation of .158 between salary and cash flow per share (CFPS); a weak positive correlation of .159 between salary and net profit margin (NPM); a weak negative correlation of -.16 between salary and common stocks outstanding (CSO); a weak negative correlation of .230 between salary and book value of common stocks outstanding (BVCSO); and a moderate positive correlation of .462 between salary and market value of common stocks outstanding (MVCSO). In addition, it was found that correlation between NPM and MVCSO was .330 which indicated that both variables had different levels (weak and moderate positive ratios) of influence to salary model.
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In NYSE large population, correlation results had shown a weak positive correlation of .205 between bonus and return on assets (ROA); a weak negative correlation of -.041 between bonus and return on equity (ROE); a weak positive correlation of .059 between bonus and earnings per share (EPS); a weak negative correlation of -.124 between bonus and cash flow per share (CFPS); a weak positive negative of -.076 between bonus and net profit margin (NPM); a weak positive negative of -.076 between bonus and common stocks outstanding (CSO); a weak negative correlation of -.124 between bonus and book value of common stocks outstanding (BVCSO); and a weak positive correlation of .100 between bonus and market value of common stocks outstanding (MVCSO). In addition, it was found that correlation between NPM and MVCSO was .394 which indicated that both variables had different levels (weak negative and weak positive ratios) of influence to bonus model.
T-tests: In TSX/S&P small population, t-tests between salary, ROA, EPS, CFPS, NPM, and CSO had resulted in accepting respective null hypotheses, indicated variable means were different. In contrast, t-tests between ROE, BVCSO, and MVCSO had resulted in rejecting respective null hypotheses, indicated variable means were same. The t-tests between bonus, BVCSO and MVCSO had resulted in rejecting respective null hypotheses, indicated variable means were same. In contrast, t-tests between bonus, ROA, ROE, EPS, CFPS, NPM, and CSO, had resulted in accepting respective null 142 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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hypotheses, indicated variable means were different. In NYSE small population, t-tests between salary, ROA, ROE, EPS, CFPS, NPM, and CSO, BVCSO, MVCSO, had resulted in accepting respective null hypotheses, indicated variable means were different. The t-tests between bonus, ROA, ROE, EPS, CFPS, NPM, and MVCSO, had resulted in accepting respective null hypotheses, indicated variable means were different. In contrast, t-tests between bonus, CSO, and BVCSO had resulted in rejecting respective null hypothesis, indicated variable means were same.
In TSX/S&P and NYSE medium populations, t-tests between salary, bonus, ROA, ROE, EPS, CFPS, NPM, CSO, and BVCSO, and MVCSO, had resulted in accepting respective null hypotheses, indicated variables means were different. In TSX/S&P large population, t-tests between salary, ROE, BVCSO, and MVCSO had resulted in rejecting respective null hypotheses, indicated variable means were same. In contrast, t-tests between salary, ROA, EPS, CFPS, NPM, and CSO had resulted in accepting respective null hypotheses, indicated variable means were different. The t-tests between bonus, ROA, ROE, EPS, CFPS, NPM, and CSO, BVCSO, and MVCSO, had resulted in accepting respective null hypotheses, indicated variable means were different. In NYSE large population, t-tests between salary, ROA, ROE, CFPS, NPM, and BVCSO, had resulted in accepting respective null hypotheses, indicated variable means were different. In contrast, t-tests between salary, EPS, CSO, and MVCSO had resulted in rejecting respective null hypotheses, indicated variable means were same. The t-tests 143 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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between bonus, ROA, ROE, EPS, CFPS, NPM, CSO, and MVCSO, had resulted in accepting respective null hypotheses, indicated variable means were different. In contrast, t-test between bonus and BVCSO, had resulted in rejecting the null hypotheses, indicated variable means were same.
Collinearity diagnostics: The collinearity test assessed the extent of correlation between independent variables. It was based on a tolerance level12, variance inflation factor (VIF)13, eigenvalues14, and condition index15. The twelve statistical model test results between CEO salary, CEO bonus, return on assets, return on equity, earnings per share, cash flow per share, net profit margin, common stocks outstanding, book value of common stocks outstanding, and market value of common stocks outstanding had indicated that they were within defined respective relevant ranges. As such, multicollinearity16 was not a concern in all twelve models.
12 Tolerance level should be within .95 or 95% confidence interval limit. 13 It measures severity of multicollinearity in regression analysis. It should be less than 5 to avoid multicollinearity concern. 14 Eigenvalues close to zero indicate a multicollinearity problem. 15 If condition index is 15, multicollinearity is a concern, and if it is greater than 30, multicollinearity is a very serious concern. 16 When a regressor is nearly a linear combination of other regressors in the model, affected estimates are unstable and have high standard errors.
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Model validity: A valid model requires a variance of residuals that are homogeneous across predicted values, known as homoscedasticity. If model is well fitted, there should be no pattern to residuals plotted against fitted values. If the variance of residuals is non-constant then residual variance is said to be heteroscedastic. In this research, graphical methods (histogram and scatter plots) were used to detect heteroscedasticity between salary, bonus, return on assets, return on equity, earnings per share, cash flow per share, net profit margin, common stocks outstanding, book value of common stocks outstanding, and market value of common stocks outstanding, among TSX/S&P and NYSE small, medium, large, and total populations. It was found from these graphical results that there wasn’t any concern of existence of hetroscedasticity as such, all twelve models were described as homoscedastic.
Model linearity: A linear regression test assumes that the relationship between response and predictor variables is linear. It is conducted by drawing a straight line on data points. In this research, linearity assumption was assessed from the normal probability plot of regression-standardized residual. It was found that in all twelve statistical results, expected and observed probabilities were not divergent to the extent of showing curved band or a big wave shaped curve as such, relationships between salary, bonus, return on assets, return on equity, earnings per share, cash flow per share, net profit margin, 145 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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common stocks outstanding, book value of common stocks outstanding, and market value of common stocks outstanding, among TSX/S&P and NYSE small, medium, large, and total populations were close to linear. In addition, histograms had shown normal distributions. 4.5.3 Operational Hypothesis Statement 3 H0 :
Among TSX/S&P and NYSE companies, there is no relationship between CEO cash compensation (salary and cash bonus) and CEO power (CEO age, CEO total stocks, CEO total value of stocks, CEO tenure, CEO turnover, 5% management stock ownership, and 5% individual/institutional stock ownership).
H1 :
Among TSX/S&P and NYSE companies, there is a relationship between CEO cash compensation (salary and cash bonus) and CEO power (CEO age, CEO total stocks, CEO total value of stocks, CEO tenure, CEO turnover, 5% management share ownership, and 5% individual/institutional stock ownership).
For operational hypothesis statement 3, separate models were developed for each dependent variable:
Salary:
Y1=c+ B1X1+B2X2+B3X3+B4X4+B5X5+B6X6+B7X7+
Bonus:
Y2=c+ B1X1+B2X2+B3X3+B4X4+B5X5+B6X6+B7X7+
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(Y1=salary; Y2=bonus; c=constant predictor; B1=influential factor for CEO age; B2=influential factor for CEO total stock holdings; B3=influential factor for total value of CEO stocks; B4=influential factor for CEO tenure; B5=influential factor for CEO turnover; B6=influential factor for 5% management stock ownership; B7= influential factor for 5% individual/institutional stock ownership; and
=error).
Let X1=value of CEO age; X2=value of CEO total stock holdings; X3=value of total value of CEO stocks; X4=value of CEO tenure; X5=value of CEO turnover; X6=value of 5% management stock ownership; and X7=value of 5% individual/institutional stock ownership.
Confidence level (α ) was set at 5 percent. df=degree of freedom Weak ratio=+/- .000 to .249; moderate ratio=+/- .250 to .499; good ratio=+/- .500 to .749 strong ratio=+/- .750 to 1.000 4.5.3.1 CEO Cash Compensation vs. CEO Power (TSX/S&P & NYSE Small, Medium, and Large Populations) The purpose of this section was to understand the nature and extent of the relationship between CEO cash compensation and CEO power. Twelve statistical models were tested based on firm sizes of small, medium, large from TSX/S&P and NYSE indexes. 147 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Each statistical model consisted of forty companies. The comprehensive results were provided in Appendix D section 3.1 to 3.12 for review.
Analysis of Variance (ANOVA): The following table summarized ANOVA findings between CEO salary, CEO bonus, and CEO power of TSX/S&P index companies:
Table 4.5.3.1A ANOVA (TSX/S&P - CEO cash compensation vs. CEO power) Small Medium Large Salary vs. CEO power
F(7,230)=8.844 p=.000 R2=0.212
F(7,232)=5.822 p=.000 R2=0.149
F(7,225)=5.768 p=.000 R2=0.152
Bonus vs. CEO power
F(7,203)=5.962 p=.000 R2=0.171
F(7,219)=2.763 p=.009 R2=0.024
F(7,228)=2.720 p=.010 R2=0.08
The results indicated that there was relationships between CEO salary, CEO bonus, and CEO power among all six models as such, operational null hypotheses were rejected at α=.05. The regression (R2) was found to be ranged from weak ratios across all six firm sizes. The following table summarized ANOVA findings between CEO salary, CEO bonus, and CEO power of NYSE index companies:
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Table 4.5.3.1B ANOVA (NYSE - CEO cash compensation vs. CEO power) Small Medium Large F(7,230)=8.844 F(7,225)=10.053 F(7,227)=5.497 Salary vs. p=.000 p=.000 p=.000 CEO power R2=0.212 R2=0.238 R2=0.145 F(7,227)=1.838 F(7,227)=1.482 F(7,215)=2.681 Bonus vs. p=.081 p=.174 p=.011 CEO power R2=0.054 R2=0.044 R2=0.08
The results indicated that there was relationships between CEO salary, CEO bonus, and CEO power among all six models, except for the relationship between CEO bonus and CEO power in medium sized companies as such, operational null hypotheses were rejected at α=.05. The regression (R2) was found to be ranged from weak ratios across all six firm sizes.
Correlations: In TSX/S&P small population, correlation results had shown a weak positive correlation of 0.16 between salary and CEO age; a weak negative correlation of -.099 between salary and CEO total stock holdings; a weak positive correlation of .218 between salary and total value of CEO stocks; a weak positive correlation of .097 between salary and CEO tenure; a good positive correlation of .63 between salary and CEO turnover; a weak positive correlation of .124 between salary and 5% management stock ownership;
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and a moderate positive correlation of .309 between salary and 5% individual/institutional stock ownership.
In TSX/S&P small population, correlation results had shown a weak positive correlation of 0.173 between bonus and CEO age; a weak negative correlation of -.140 between bonus and CEO total stock holdings; a weak positive correlation of .215 between bonus and total value of CEO stocks; a weak positive correlation of .053 between bonus and CEO tenure; a weak negative correlation of -.123 between bonus and CEO turnover; a weak positive correlation of .104 between bonus and 5% management stock ownership; and a weak positive correlation of .007 between bonus and 5% individual/institutional stock ownership.
In NYSE small population, correlation results had shown a weak positive correlation of 0.096 between salary and CEO age; a weak negative correlation of -.162 between salary and CEO total stock holdings; a weak positive correlation of .236 between salary and total value of CEO stocks; a weak negative correlation of -.074 between salary and CEO tenure; a weak positive correlation of .132 between salary and CEO turnover; a weak positive correlation of .079 between salary and 5% management stock ownership; and a weak positive correlation of .159 between salary and 5% individual/institutional stock ownership.
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In NYSE small population, correlation results had shown two hundred and eleven observations were selected and the remaining nineteen observations were deleted due to outliers. The Pearson’s correlation results had shown a weak negative correlation of .004 between bonus and CEO age; a weak negative correlation of -.178 between bonus and CEO total stocks; a weak negative correlation of -.134 between bonus and total value of CEO stocks; a weak negative correlation of -.086 between bonus and CEO tenure; a weak positive correlation of .09 between bonus and CEO turnover; a weak negative correlation of -.09 between bonus and 5% management stock ownership; and a good positive correlation of .67 between bonus and 5% individual/institutional stock ownership.
In TSX/S&P medium population, correlation results had shown a weak positive correlation of 0.054 between salary and CEO age; a weak negative correlation of -.034 between salary and CEO total stock holdings; a weak negative correlation of -.131 between salary and total value of CEO stocks; a moderate positive correlation of .264 between salary and CEO tenure; a weak positive correlation of .159 between salary and CEO turnover; a weak positive correlation of .045 between salary and 5% management stock ownership; and a weak negative correlation of -.062 between salary and 5% individual/institutional stock ownership.
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In TSX/S&P medium population, correlation results had shown a moderate positive correlation of .40 between bonus and CEO age; a weak positive correlation of .155 between bonus and CEO total stock holdings; a weak positive correlation of .106 between bonus and total value of CEO stocks; a weak positive correlation of .138 between bonus and CEO tenure; a weak negative correlation of -.088 between bonus and CEO turnover; a weak positive correlation of .154 between bonus and 5% management stock ownership; and a weak negative correlation of -.180 between bonus and 5% individual/institutional stock ownership.
In NYSE medium population, correlation results had shown a moderate positive correlation of 0.367 between salary and CEO age; a weak negative correlation of -.111 between salary and CEO total stock holdings; a moderate negative correlation of -.41 between salary and total value of CEO stocks; a weak positive correlation of .232 between salary and CEO tenure; a weak negative correlation of -.225 between salary and CEO turnover; a weak negative correlation of -.238 between salary and 5% management stock ownership; and a weak negative correlation of -.03 between salary and 5% individuals/institutional stock ownership.
In NYSE medium population, correlation results had shown a weak negative correlation of -.102 between bonus and CEO age; a weak negative correlation of -.155 between bonus and CEO total stock holdings; a weak negative correlation of -.137 between 152 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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bonus and total value of CEO stocks; a weak negative correlation of -.064 between bonus and CEO tenure; a weak positive correlation of .02 between bonus and CEO turnover; a weak negative correlation of -.047 between bonus and 5% management stock ownership; and a weak negative correlation of -.001 between bonus and 5% individuals/institutional stock ownership.
In TSX/S&P large population, correlations results had shown a weak positive correlation of 0.111 between salary and CEO age; a moderate positive correlation of .347 between salary and CEO total stock holdings; a weak positive correlation of .210 between salary and total value of CEO stocks; a weak positive correlation of .105 between salary and CEO tenure; a weak positive correlation of .105 between salary and CEO turnover; a weak positive correlation of .001 between salary and 5% management stock ownership; and a weak negative correlation of -.018 between salary and 5% individuals/institutional stock ownership.
In TSX/S&P large population, correlation results had shown a weak positive correlation of .05 between bonus and CEO age; a weak positive correlation of .169 between bonus and CEO total stock holdings; a weak positive correlation of .226 between bonus and total value of CEO stocks; a weak negative correlation of -.037 between bonus and CEO tenure; a weak negative correlation of -.027 between bonus and CEO turnover; a weak positive correlation of .101 between bonus and 5% management stock ownership; 153 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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and a weak positive correlation of .08 between bonus and 5% individuals/institutional stock ownership.
In NYSE large population, correlation results had shown a weak positive correlation of 0.136 between salary and CEO age; a weak positive correlation of .033 between salary and CEO total stock holding; a weak positive correlation of .154 between salary and total value of CEO stocks; a weak positive correlation of .178 between salary and CEO tenure; a weak positive correlation of .166 between salary and CEO turnover; a weak negative correlation of -.08 between salary and 5% management stock ownership; and a weak negative correlation of -.176 between salary and 5% individual/institutional stock ownership.
In NYSE large population, correlation results had shown a weak positive correlation of .05 between bonus and CEO age; a weak negative correlation of -.017 between bonus and CEO total stock holdings; a weak positive correlation of .06 between bonus and total value of CEO stocks; a weak negative correlation of -.012 between bonus and CEO tenure; a weak negative correlation of -.002 between bonus and CEO turnover; a weak positive correlation of .143 between bonus and 5% management stock ownership; and a weak negative correlation of -.157 between bonus and 5% individuals/institutional stock ownership.
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T-tests: In TSX/S&P small population, t-tests between salary, bonus, CEO age, CEO tenure, CEO turnover, and 5% management stock ownership had resulted in accepting respective null hypotheses, indicated that the variable means were different. In contrast, t-tests between salary, CEO total stock holdings, total value of CEO stocks, and 5% individual/institutional ownership had resulted in rejecting respective null hypotheses, indicated that the variable means were same. In NYSE small population, t-tests between salary, CEO tenure, CEO turnover, CEO total stock holdings, and 5% management stock ownership had resulted in accepting respective null hypotheses, indicated that the variable means were different. In contrast, t-tests between salary, CEO age, total value of CEO stocks, and 5% individual/institutional ownership had resulted in rejecting respective null hypotheses, indicated that the variable means were same. The t-tests between bonus, CEO age, CEO tenure, CEO turnover, and 5% management stock ownership, and 5% individual/institutional ownership had resulted in accepting respective null hypotheses, indicated that the variable means were different. In contrast, t-tests between bonus, CEO total stock holdings and total value of CEO stocks had resulted in rejecting respective null hypotheses, indicated that the variable means were same.
In TSX/S&P medium population, t-tests between salary, CEO age, CEO tenure, total value of CEO stocks, and 5% management ownership had resulted in rejecting 155 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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respective null hypotheses, indicated that the variable means were same. In contrast, the t-tests between salary, CEO turnover, and 5% individual/institutional ownership had resulted in accepting respective null hypotheses, indicated that the variable means were different. The t-tests between bonus, CEO age, CEO total stocks, CEO total value of stocks, CEO tenure, and CEO turnover had resulted in accepting respective null hypotheses, indicated that the variable means were different. In contrast, the t-tests between bonus, 5% management stock ownership, and 5% individual/institutional ownership had resulted in rejecting respective null hypotheses, indicated that the variable means were different. In NYSE medium population, t-tests between salary, CEO age, CEO turnover, and 5% management ownership had resulted in rejecting respective null hypotheses, indicated that the variable means were same. In contrast, the t-tests between salary, CEO total stock holdings, total value of CEO stocks, CEO tenure, and 5% individual/institutional had resulted in accepting respective null hypotheses, indicated that the variable means were different. The t-tests between bonus, CEO age, total value of CEO stocks, CEO tenure, CEO turnover, CEO total stock holdings, 5% management ownership, and 5% individual/institutional ownership had resulted in accepting respective null hypotheses, indicated that the variable means were different.
In TSX/S&P large population, t-tests between salary, CEO total stock holdings, and total value of CEO stocks, had resulted in rejecting respective null hypotheses, indicated that 156 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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the variable means were same. In contrast, t-tests between salary, CEO age, CEO tenure, CEO turnover, and 5% management stock ownership, and 5% individual/institutional ownership had resulted in accepting respective null hypotheses, indicated that the variable means were different. The t-tests between bonus, CEO age, CEO tenure, CEO turnover, and 5% management stock ownership, and 5% individual/institutional ownership had resulted in accepting respective null hypotheses, indicated that the variable means were different. In contrast, t-tests between bonus, CEO total stock holding and total value of CEO stocks had resulted in rejecting respective null hypotheses, indicated that the variable means were same. In NYSE large population, t-tests between bonus, CEO age, CEO turnover, and 5% management stock ownership, had resulted in accepting respective null hypotheses, indicated that the variable means were different. In contrast, t-tests between salary, CEO tenure, CEO total stock holdings, total value of CEO stocks, and 5% individual/institutional ownership, had resulted in rejecting respective null hypotheses, indicated that the variable means were same. The t-tests between bonus, CEO age, CEO tenure, CEO turnover, and 5% management stock ownership, and 5% individual/institutional ownership had resulted in accepting respective null hypotheses, indicated that the variable means were different. In contrast, t-tests between bonus, CEO total stock holdings, and total value of CEO stocks, had resulted in rejecting respective null hypotheses, indicated that the variable means were same.
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Collinearity diagnostics: The collinearity test assessed the extent of correlation between independent variables. It was based on a tolerance level17, variance inflation factor (VIF)18, eigenvalues19, and condition index20. The twelve statistical model test results between CEO salary, CEO bonus, CEO age, CEO total stock holdings, total value of CEO stocks, CEO tenure, CEO turnover, 5% management share ownership, and 5% individual/institutional stock ownership had indicated that they were within defined respective relevant ranges. Therefore, multicollinearity21 was not a concern in all twelve models.
Model validity: A valid model requires a variance of residuals that are homogeneous across predicted values, known as homoscedasticity. If model is well fitted, then there should be no pattern to residuals plotted against fitted values. If the variance of residuals is nonconstant then residual variance is said to be heteroscedastic. In this research, graphical methods (histogram and scatter plots) were used to detect heteroscedasticity between salary, bonus, CEO age, CEO total stock holdings, total value of CEO stocks, CEO tenure, CEO turnover, 5% management share ownership, and 5% individual/institutional 17 Tolerance level should be within .95 or 95 percent confidence interval limit. 18 It measures severity of multicollinearity in regression analysis. It should be less than 5 to avoid multicollinearity concern. 19 Eigenvalues close to zero indicate a multicollinearity problem. 20 If condition index is 15, multicollinearity is a concern, and if it is greater than 30, multicollinearity is a very serious concern. 21 When a regressor is nearly a linear combination of other regressors in the model, affected estimates are unstable and have high standard errors.
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stock ownership, among TSX/S&P and NYSE small, medium, large, and total populations. It was found from these graphical results that there wasn’t any concern of existence of hetroscedasticity as such, all twelve models were described as homoscedastic.
Model linearity: The linear regression test assumed that the relationship between response and predictor variables is linear. It is conducted by drawing a straight line on data points. In this research, linearity assumption was assessed from the normal probability plot of regression-standardized residual. It was found that all statistical models expected and observed probabilities were not divergent to the extent of showing a curved band or a big wave shaped curve, as such, relationships between salary, bonus, CEO age, CEO total stock holdings, total value of CEO stocks, CEO tenure, CEO turnover, 5% management share ownership, and 5% individual/institutional stock ownership, among TSX/S&P and NYSE small, medium, large, and total populations were close to linear. In addition, histograms had shown normal distributions.
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CHAPTER FIVE SYNTHESIS
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CHAPTER FIVE - SYNTHESIS 5.0 CHAPTER INTRODUCTION The primary purpose of this research study was to understand respective CEO cash compensation systems of TSX/S&P and NYSE indexes companies. This research was based on three research questions. The first question was: among TSX/S&P and NYSE indexes companies, is there a relationship between CEO cash compensation and firm size?. The second research question was: among TSX/S&P and NYSE indexes companies, is there a relationship between CEO cash compensation and firm performance?. The third research question was: among TSX/S&P and NYSE indexes companies, is there a relationship between CEO cash compensation and CEO power?. The presentation of this thesis and its reasoned defense will be based on detailed discussion of the effect of firm size on the relationship between CEO cash compensation, firm size, firm performance, and CEO power, among TSX/S&P and NYSE populations. The previous research and current research results will be discussed and compared to understand clearly the nature and extent of correlations between sub variables. The end part of this chapter will be a presentation of new theories on the relationship between CEO cash compensation, firm size, firm performance, and CEO power, based on the combined results of TSX/S&P and NYSE
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populations. Overall, this chapter presentation will demonstrate originality, quality, and the depth of research performed.
5.1 SYNTHESIS: CEO CASH COMPENSATION AND FIRM SIZE It was found that eleven of twelve statistical models had a p-value of less than .05, that is, they were statistically significant, therefore null hypotheses were rejected. The accepted null hypothesis was the relationship between CEO bonus and firm size in NYSE medium sized companies, indicated that there was no relationship found between them. Previous studies indicated that, there was a relationship between CEO compensation and firm size. For example, Gomez-Mejia and Barkema (1998) defined the relationship as a positive relationship between CEO compensation and firm size. Finkelstein and Hambrick (1996) found that firm size was related to the level of executive compensation. Sigler (2011) stated that firm size appeared to be the most significant factor in determining CEO compensation. Overall, previous and this research study results had a relationship between CEO cash compensation and firm size. However, this research study was conducted based on different firm sizes to understand their effects on the extent of the relationship between CEO cash, CEO bonus, and firm size.
The correlation results had shown there were positive correlations between CEO salary, CEO bonus, and total sales, among TSX/S&P and NYSE populations. In TSX/S&P 162 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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population, the correlation between CEO salary and total sales had decreased from .574 to .477 and then had decreased further to .297, as firm size had changed from small to medium and to large. Likewise, in NYSE population, the correlations between CEO salary and total sales had decreased from .575 to .107 and then had increased to .422, as firm size had changed from small to medium and to large. In TSX/S&P population, the correlations between bonus and total sales had decreased from .358 to .25 and then had increased to .32, as firm size had changed from small to medium and to large. In NYSE population, the correlations between bonus and total sales had decreased from .121 to .027 and then had decreased further to -.15, as firm size changed from small to medium and to large. Thus, these results had shown that firm size had a negative influence on the correlation between CEO salary, CEO bonus, and total sales, among TSX/S&P and NYSE companies. That is, the board expected the organization to operate at optimal efficiency as such, CEO actions became less of a milestone for board to reward CEO with high cash compensation, or board selected to reward the CEO on an equity basis. The study conducted by Tosi, Werner, Katz, and Gomez-Mejia (2000) found that the estimated correlation between CEO compensation and firm size was .643, which indicated that firm size accounts for over 40% of variance in CEO pay. In addition, they found that the adjusted composite correlation between change in CEO pay and change in firm size was .225, accounting for about 5% of variance in changes in CEO pay. Similarly, Deckop (1988) stated that CEO compensation was positively related to profit as a percentage of sales. Overall, previous 163 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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and this research study results were positively correlated between CEO cash compensation and total sales but the extent of positive correlations were in disagreement. In addition, this research study was conducted based on firm size perspective as such the results were more articulate.
The correlation results had shown there were mixed correlations between CEO salary, CEO bonus, and total employees, among TSX/S&P and NYSE populations. In TSX/S&P population, the correlation between CEO salary and total number of employees had decreased from .54 to .029 and then had decreased further to -.083, as firm size had changed from small to medium and to large. Likewise, in NYSE population, the correlation between CEO salary and total number of employees had decreased from .542, to -.208, and then had increased to .407, as firm size had changed from small to medium and to large. In TSX/S&P population, the correlation between CEO bonus and total number of employees had decreased from .125 to -.019 and then had increased to .112, as firm size had changed from small to medium and to large. In NYSE population, the correlation between CEO bonus and total number of employees had decreased from .121 to .027 and then had decreased further to -.15, as firm size had changed from small to medium and to large. Therefore, these results had indicated that firm size had influenced negatively the correlation between CEO salary, CEO bonus, and total number of employees. That is, the board expected the organization to operate at optimal efficiency as such, CEO actions became less of a 164 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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milestone for board to reward CEO with high cash compensation, or board selected to reward the CEO on an equity basis. The study conducted by Gomez-Mejia and Barkema (1998) found that CEOs cash incentives had a strong relationship with firm size as CEOs of large companies make higher income than CEOs of small companies. This was supported by Tosi and Gomez-Mejia (1994), who argued that measurement of firm size was a composite score of standardized values of reported total sales and number of employees. In addition, they believed that a host of structural factors and pragmatic problems make it difficult for corporations to effectively control executives, leading to compensation packages that are more closely tied to firm size than performance. Finkelstein and Boyd (1998) and Sanders and Carpenter (1998) reported correlations of .62, .50, and .42, respectively in their previous studies on CEO compensation and firm size. However, studies conducted by Belkaoui and Picur (1993), David, Koachhar, and Levitas (1998), and Gray and the Cannella (1997) found correlations as low as .107, .110, and .170, respectively. Overall, previous studies’ and this research study’s results were divergent. That is, the previous study's results were ranged from weak to good positive ratios, whereas, this research study’s results were ranged from weak negative to good positive ratios. In conclusion, statistical model results had led to the development of the first theory: there is a mixed correlation between CEO salary, CEO bonus, and firm size. In addition, the large firm size will have a negative impact on the correlation between them. That is, the board expected the organization to operate at optimal efficiency therefore, CEO actions became less of a 165 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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milestone for the board to reward the CEO with a high cash compensation, or the board selected to reward the CEO on an equity basis.
5.2 SYSTHESIS: CEO CASH COMPENSATION AND FIRM PERFORMANCE It was found that eleven of twelve statistical models had a p-value of less than .05, that is, they were statistically significant as such null hypotheses were rejected. The accepted null hypothesis was the relationship between CEO bonus and firm performance in NYSE large sized companies, indicated that there was no relationship found between them. The study conducted by Mehran (1995) reported that CEO pay structure was positively related to same year performance. This is supported by Gibbons and Murphy (1990), who found that CEOs salaries and bonuses were positively and significantly related to firm performance. This is further supported by Blanchard, Lopez-de-Silanes and Shleifer (1994), Iyengar, Raghavan J. (2000), and Bertrand and Mullainathan (2001), who found that CEO cash compensation had increased when firm profits rise for reasons that have nothing to do with managers’ efforts. On the other hand, Loomis (1982) argued that CEO pay was unrelated to performance. This is supported by Henderson and Fredrickson (1996) and Sanders and Carpenter (1998, 2002), who believed that CEO pay might be unrelated to performance but it related to the organizational complexity that they managed. Overall, previous research and this research’s results had found the relationship between CEO cash 166 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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compensation and firm performance, but the extent of correlations between sub variables were divergent due to different sample size, population, statistical method, and variables used in the statistical model. In addition, previous studies had rarely used firm size as a control variable to understand the relationship between CEO compensation and firm performance.
The correlation results had shown there were mixed correlations between CEO salary, CEO bonus, and return on assets, among TSX/S&P and NYSE populations. In TSX/S&P population, the correlation between CEO salary and ROA had increased from .074 to .100 and then had decreased to .025, as firm size had changed from small to medium and to large. Likewise, in NYSE population, the correlation between CEO salary and ROA had increased from -.068 to .005 and then had increased further to .108, as firm size had changed from small to medium and to large. However, reversed pattern was observed in TSX/S&P population for CEO bonus, that is, the correlation between bonus and ROA had decreased from .148 to .012 and then had decreased further to -.011, as firm size had changed from small to medium and to large. However, in NYSE population, it had increased from .039 to .117 and then had increased further to .205, as firm size had changed from small to medium and to large. In TSX/S&P population, large firm size had increased the correlation between CEO salary, CEO bonus, and ROA. In contrast, in NYSE population, large firm size had decreased the correlation between CEO salary, CEO bonus, and ROA. As such, firm size effect on the 167 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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correlation between them will depend on design and culture of the CEO compensation system of a particular market. The study conducted by Werner, Katz and Gomez-Mejia (2000) found that estimated true correlation between CEO pay and ROA was 0.117. Leone et al. (2006) found that there was no difference in CEO pay performance sensitivity to changes in ROA based on positive and negative stock returns. However, Antle and Smith (1986) found a strong correlation between CEO compensation and ROA. They reasoned their finding to direct links between ROA and CEO pay from CEO contract. This was supported by Shaw and Zhang (2010), who found that CEO cash compensation was significantly positively correlated with return on assets and stock returns, indicated that CEOs of better performing firms were rewarded with higher pay. On the other hand, Mehran (1995) found that ROA was inversely related to percentage of CEOs’ total cash compensation. Overall, previous studies and this research study results were divergent. That is, previous studies had shown inconsistency in their results ranged from weak negative to strong positive correlations between them, whereas, this research study results found weak positive ratios. In conclusion, these findings had led to the development of a second new theory: there is a weak positive correlation between CEO cash compensation and return on assets. In addition, the large firm size will have a mixed impact on the correlation between CEO cash compensation and return on assets.
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In TSX/S&P population, there were positive correlations between CEO salary, CEO bonus, and ROE. However, in NYSE population, it was found that there were mixed correlations between CEO salary, CEO bonus, and ROE. In TSX/S&P population, the correlation between CEO salary and ROE had decreased from .136 to .039 and then had increased to .186, as firm size had changed from small to medium and to large. In contrast, in NYSE population, the correlation between CEO salary and ROE had increased from -.148 to .015 and then had decreased to .012, as firm size had changed from small to medium and to large. In TSX/S&P population, the correlation between CEO bonus and ROE had decreased from .134 to .075 and then had increased to .013, as firm size had changed from small to medium and to large. However, in NYSE population, the correlation between CEO bonus and ROE had increased from -.051 to .065 and then had decreased to -.041, as firm size had changed from small to medium and to large. In addition, the large firm size had a positive impact on the correlation between CEO cash compensation and return on equity. The study conducted by Finkelstein and Boyd (1998) found that the correlations between ROE, CEO cash compensation, and long-term pay were .13 and -.03, respectively. Similarly, Johnson (1982) found that the correlation between executive pay and ROE was .003. On the other hand, Belliveaus, O’Reilly, and Wade (1996) found that the correlation between ROE and CEO pay was .410. This was supported by Mehran (1995), who found that CEO compensation in companies was relatively sensitive to firm performance tend to produce high returns for shareholders than in companies the correlation between CEO 169 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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pay and firm performance was weak. Shaw and Zhang (2010) found that changes in CEO cash compensation had a significantly positive correlation with stock returns, indicated CEOs of better performing firms were rewarded with high pay. On the other hand, Finkelstein and Hambrick (1989) found that ROE was unrelated to salary but positively related to bonus. Overall, previous studies and this research study’s results had shown there was a weak mixed correlation between CEO compensation and return on equity. That is, the correlations were ranged from weak negative to weak positive ratios. However, this research study was conducted based on firm size perspective, as such, the results were more articulate. In conclusion, this research finding had led to the development of third new theory: there is a weak mixed correlation between CEO cash compensation and return on equity. That is, the correlation between them will depend on the importance of return on equity on CEO performance criteria. In addition, the large firm size will have a mixed impact on the correlation between CEO cash compensation and return on equity.
The correlation results had shown there were weak mixed correlations between CEO salary, CEO bonus, and EPS, among TSX/S&P and NYSE populations. In TSX/S&P population, the correlation between CEO salary and EPS had decreased from .036 to .005 and then had decreased further to -.10, as firm size had changed from small to medium and to large. In contrast, in NYSE population, the correlation between CEO salary and EPS had increased from -.052 to .103 and then had increased further to 170 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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.207, as firm size had changed from small to medium and to large. In TSX/S&P population, the correlation between CEO Bonus and EPS had increased from -.008 to .054 and then had decreased to -.057, as firm size had changed from small to medium and to large. Similarly, in NYSE population, the correlation between CEO Bonus and EPS had decreased from .05 to -.008 and then had increased to .059, as firm size had changed from small to medium and to large. In addition, the effect of firm size on the correlation between them had depended on the design and culture of the CEO compensation system of a particular market. It was understood from the literature that, previous research studies had lacked publications on the correlation between CEO cash compensation and the EPS. However, EPS was indirectly discussed with studies on firm earnings, firm accounting policies, stock compensation, and CEO wealth. For example, Gaver et al. (1995) and Holthausen et al. (1995a) found that executives manage earnings downward when their reported performance exceeds maximum, but had shown that executives managed earnings upward when below threshold. Conyon et al. (2000) and Murphy (1999, 2000) believed that compensation contracts linking rewards to performance provide executives with direct and potentially powerful incentives to manage reported EPS. Indjejikian and Nanda (2002) believed that executive may also smooth performance in the incentive zone if pay for performance relation was concave above standard but convex below. Gerhart et al. (2009) believed that earnings were imperfectly related to shareholder return primarily due to the fact that CEO specific wealth was generated via equity positions. Overall, previous studies had 171 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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discussed the correlations between EPS and CEO pay on a theoretical basis as such had lacked empirical results to compare with this research findings. In conclusion, this research finding had led to the development of fourth new theory: there is a weak mixed correlation between CEO salary, CEO bonus, and earnings per share. That is, the correlation between them will depend on the firm’s earnings and extent of short-term CEO incentives. In addition, the effect of the firm size on the correlation between them will depend on the design and culture of the CEO compensation system of a particular market.
The correlation results had shown that there were mixed correlations between CEO salary, CEO bonus, and CFPS, among TSX/S&P and NYSE populations. In TSX/S&P population, the correlation between CEO Salary and CFPS had increased from -.02 to .028 and then had decreased to -.008, as firm size had changed from small to medium and to large. In contrast, in NYSE population, the correlation between CEO salary and CFPS had increased from .05 to .142 and then had increased further to .158, as firm size had changed from small to medium and to large. In TSX/S&P population, the correlation between CEO bonus and CFPS had decreased from .053 to -.022 and then had increased to -.015, as firm size had changed from small to medium and to large. Similarly, in NYSE population, the correlation between CEO bonus and CFPS had increased from -.066 to .029 and then had decreased to -.012, as firm size had changed from small to medium and to large. In addition, firm size effect on the correlation 172 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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between them had depended on design and culture of the CEO compensation system of a particular market. The study conducted by Iyengar (2000) found that the level of CEO’s cash compensation was positively related to the firms’ level of operating cash flows but was unrelated to either accounting or market performance. However, Kumar et al. (1993) and Natarajan (1996) didn’t find a significant association between cash flows from operations and CEO compensation after controlling for net income. In contrast, Yang et al. (2006) found that cash flows from operations were compensation contract relevant. Overall, previous studies and this research study’s results were divergent. That is, previous studies had found a positive correlation between CEO compensation and cash flow per share but the extent of correlation was in disagreement. However, this research study’s findings had ranged from weak negative to weak positive ratios. In conclusion, this research results had led to the development of fifth new theory: there is a weak mixed correlation between CEO salary, CEO bonus, and cash flow per share. That is, the correlation between them will depend on the firm’s balance of operating cash flow and board decision to reward based on extent of cash over stock options. In addition, the effect of firm size on the correlation between them will depend on design and culture of the CEO compensation system of a particular market.
The correlation results had shown that there were positive correlations between CEO salary, CEO bonus, and NPM, among TSX/S&P and NYSE populations. In TSX/S&P population, the correlation between CEO salary and NPM had increased from .077 to 173 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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.182 and then had increased further to .427, as firm size had changed from small to medium and to large. Similarly, in NYSE population, the correlation between CEO salary and NPM had increased from -.123 to .118 and then had increased further to .159, as firm size had changed from small to medium and large. In TSX/S&P population, the correlation between CEO bonus and NPM had increased from .111 to .142 and then had increased further to .527, as firm size had changed from small to medium and to large. In NYSE population, the correlation between CEO bonus and NPM had increased from -.076 to .23 and then had decreased to .124, as firm size had changed from small to medium and to large. In addition, firm size had a positive effect on the correlation between the CEO cash compensation and NPM. The study conducted by Healy (1985), Lambert and Larcker (1987), Pavlick et al. (1983), and Verrechia (1986) stated that incentive scheme based on accounting performance measure appear to influence accounting earnings. Lambert and Larcker (1987) argued that firms place relatively more weight on market performance than on accounting performance measures in compensation contracts for situations in which variance of accounting performance was high relative to market performance measures; the firm was experiencing a high rate of growth; and manager’s holdings of the firm’s stock were low. Jensen and Murphy (1990) found that the average pay increase for a CEO whose shareholders gain $400 million was $37,300, compared to an average pay increase of $26,500 for a CEO whose shareholders lose $400 million. Blanchard, Lopez-de-Silanes and Shleifer (1994), and Bertrand and Mullainathan (2001) found that CEO cash compensation increased when 174 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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firm profits rose for reasons that had nothing to do with managers’ efforts. Tosi, Werner, Katz and Gomez-Mejia (2000) found that the overall ratio of change in CEO pay and change in financial performance is 0.203, an accounting for about 4% of the variance. Healy (1985), Lambert and Larcker (1987), Pavlick et al. (1983), and Verrechia (1986) believed that incentive scheme based on accounting performance measure appear to influence accounting earnings. On the other hand, Antle and Smith (1986) found no relation between CEO cash compensation and firm performance. Overall, previous and this research studies results had found positive correlations but the extent of correlations between them were divergent. That is, previous research studies had a weak positive correlation between them, whereas, this research study findings ranged from weak to good positive ratios. In conclusion, these research findings had led to the development of a sixth new theory, there is a positive correlation between CEO salary, CEO bonus, and net profit margin. In addition, the large firm size will have a positive influence towards the correlation between CEO salary, CEO bonus, and net profit margin.
The correlation results had shown that in the TSX/S&P population, there were positive correlations between CEO salary, CEO bonus, and CSO. However, in NYSE population, it was found that there were mixed correlations between them. In the TSX/S&P population, the correlation between CEO salary and CSO had increased from .421 to .294 and then had decreased to .267, as firm size had changed from small to 175 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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medium and to large. Similarly, in NYSE population, the correlation between CEO salary and CSO had increased from -.085 to .192 and then had decreased to -.16, as firm size had changed from small to medium and to large. In TSX/S&P population, the correlation between CEO bonus and CSO had decreased from .491 to .240 and then had increased to .336, as firm size had changed from small to medium and to large. In contrast, in NYSE population, the correlation between CEO bonus and CSO had increased from .045 to .18 and then had decreased to -.076, as firm size had changed from small to medium and to large. In addition, the large firm size had a negative impact on the correlation between CEO salary, CEO bonus, and CSO, among TSX/S&P and NYSE populations. It was understood from the literature review that, previous research studies had lacked the focus on the relationship between CEO cash compensation and common stocks outstanding. Therefore, the results of the correlations between CEO cash compensation and common stocks outstanding were introduced for the first time in executive compensation literature. In conclusion, this research study’s results had led to the development of seventh new theory: there is a mixed correlation between CEO salary, CEO bonus, and common stocks outstanding. That is, the correlation between them will depend on firm’s equity position and ownership structure. In addition, the large firm size will have a mixed influence on the correlation between CEO cash compensation and common stocks outstanding.
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The correlation results had shown that there was a positive correlation between CEO salary, CEO bonus, and BVCSO, among TSX/S&P and NYSE populations. In TSX/S&P population, the correlation between CEO salary and BVCSO had decreased from .601 to .330 and then had decreased further to .283, as firm size had changed from small to medium, and to the Large. Likewise, in NYSE population, the correlation between CEO salary and BVCSO had decreased from .243 to .04 and then had increased to .23, as firm size had changed from small to medium and to large. In TSX/S&P population, the correlation between CEO bonus and BVCSO had decreased from .718 to .370 and then had increased to .425, as firm size had changed from small to medium and to large. In NYSE population, the correlation between CEO bonus and BVCSO had decreased from .407 to .129 and then had decreased further to .124, as firm size had changed from small to medium and to large. In addition, it had shown that, a large firm size had a negative influence on the correlation between CEO salary, CEO bonus, and BVCSO. It was understood from the literature, previous research studies had lacked focus towards understanding the correlation between CEO cash compensation and the book value of common stocks outstanding. Therefore, the results of the correlations between CEO cash compensation and the book value of common stocks outstanding were introduced for the first time in executive compensation literature. In conclusion, this research study’s results had led to the development of an eighth new theory: there is a positive correlation between CEO salary, CEO bonus, and book value of common stocks outstanding. In addition, the large firm size will have a negative influence towards the 177 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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correlation between CEO salary, CEO bonus, and book value of common stocks outstanding.
The results had shown that in TSX/S&P population there were positive correlations between CEO salary, CEO bonus, and MVCSO. However, in NYSE population, it was found that there were mixed correlations between CEO salary, CEO bonus, and MVCSO. In TSX/S&P population, the correlation between CEO salary and MVCSO had decreased from .627 to .310 and then had decreased further to .263, as firm size had changed from small to medium and to large. Similarly, in NYSE population, the correlation between salary and MVCSO had increased from .148 to .194 and then had increased further to .462, as firm size had changed from small to medium and to large. In TSX/S&P population, the correlation between CEO bonus and MVCSO had decreased from .663 to .211 and then had increased to .340, as firm size had changed from small to medium and large. In NYSE population, the correlation between CEO bonus and MVCSO had increased from -.02 to -.015 and then had further increased to .100, as firm size had changed from small to medium and to large. In addition, the results had shown that firm size had mixed impact on the correlation between CEO salary, CEO bonus, and MVCSO. That is, the relationship between them will depend on CEO contract and design and culture of the CEO compensation system of a particular market. The study conducted by Murphy (1985) and Coughlan and Schmidt (1985) found that change in executive compensation was positively related to changes in 178 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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current year stock price. In addition, they argued that although the relationship between them had statistically significant, however much of the variance in executive compensation remains unexplained. On the other hand, compensation consultants such as Bickford (1981), Ellig (1984), Rich and Larson (1984), and Decktop (1987) found that although stock prices were very sensitive to external events as such may have little to do with how efficiently a firm was ran and controlled by management. Therefore, they believed that it was more appropriate to use profitability measure as a proxy for firm performance. Jensen and Murphy (1990) and Hubbard and Palia (1995) favored performance to be measured with stockholder value to reflect CEO wealth. Overall, previous studies and this research study results were divergent. That is, previous studies had found a positive relationship between CEO compensation and MVCSO, however, this research study findings were mixed, that is, the correlations between them ranged from weak negative to good positive ratios. In conclusion this research study’s results had led to the development of ninth theory: there is a mixed correlation between CEO salary, CEO bonus, and market value of common stocks outstanding. That is, the correlation between them will depend on board decision on the extent of cash over stock compensation. In addition, the effect of firm size on the correlation between them will depend on design and culture of the CEO compensation system of a particular market.
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5.3 SYNTHESIS: CEO CASH COMPENSATION AND CEO POWER It was found that ten of twelve statistical models had a p-value of less than .05, that is, they were statistically significant as such null hypotheses were rejected. The accepted null hypotheses were the relationships between CEO bonus and firm performance in NYSE small and medium sized companies indicated that there were no relationships found between them. The study conducted by Aggarwal and Samwick (1999) and Bebchuk, Fried and Walker (2002) found that CEO power was widely believed to vary in cross section and over time. The CEOs with greater stock ownership, who possess greater tenure, and who serve at firms with larger or less independent boards, are likely to have greater power. The CEOs with more established reputations or whose actions are more difficult to judge are more likely to possess greater influence. In addition, Bebchuk, Fried and Walker (2002) believed that CEOs influence their own compensation to extract economic rents from shareholders. Overall, previous studies and this research study’s results had found a relationship between CEO cash compensation and CEO power, but the extent of correlations between sub-variables were divergent due to different sample size, population, statistical method, and variables used in the statistical model. In addition, previous studies had rarely used firm size as a control variable to understand the relationship between CEO compensation and CEO power.
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The results had shown that there were mixed correlations between CEO salary, CEO bonus, and CEO age, among TSX/S&P and NYSE populations. In TSX/S&P population, the correlation between CEO salary and CEO age had decreased from .106 to .084 and then had decreased further to .08, as firm size had changed from small to medium and to large. In NYSE population, the correlation between CEO salary and CEO age had increased from .096 to .367 and then had decreased to .136, as firm size had changed from small to medium and to large. In TSX/S&P population, the correlation between CEO bonus and CEO age had decreased from .173 to -.04 and then further had decreased to -.05, as firm size had changed from small to medium and to large. However, in NYSE population, it had increased from -.162 to -.102 and then had increased further to -.051, as firm size had changed from small to medium and to large. As such, in TSX/S&P population, the firm size had a negative influence on the correlation between CEO salary, CEO bonus, and CEO age. However, in NYSE population, the firm size had a positive influence on the relationship between CEO salary and CEO age. In contrast, the firm size had a mixed influence on the correlations between CEO bonus and CEO age. Overall, these results had indicated that CEO salary had a weak positive correlation with CEO age. That is, CEO salary had increased based on CEO experience with the firm. The CEO bonus had a weak positive correlation with CEO age. That is, it was based on primary factors such as firm performance and achievement of strategic goals. In addition, firm size had a mixed influence on the correlation between CEO salary, CEO bonus, and CEO age. The study 181 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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conducted by Deckop (1988) argued that the CEO’s age had little effect on CEO compensation. Finkelstein and Hambrick (1989) found an inverted U-shaped relationship between CEO age and CEO cash compensation. That is, CEO cash compensation had increased up to 59 years age, beyond which real cash earnings had decreased on a consistent basis till retirement. This is supported by McKnight et al. (2000) found that CEO compensation was positively related to age, but it had provided diminishing returns on marginal pay as age increased. This effect was so profound that marginal CEO compensation level decreased till CEO retirement age. Overall, previous research studies and this research study’s results were found to be divergent. That is, previous studies had found an inverted U-shaped correlation results, whereas, this research study’s results were ranged from weak negative to weak positive ratios. In conclusion, this research study’s results had led to the development of tenth theory: there is a weak to moderate positive correlation between CEO salary and CEO age, perhaps due to experience, and there is a weak positive correlation between CEO bonus and CEO age, indicating that a bonus is rewarded based on the firm’s performance and achievement of strategic goals. In addition, that firm size will have a negative influence on the correlation between CEO salary, CEO bonus, and CEO age.
The correlation results had shown that there were mixed correlations between CEO salary, CEO bonus, and CEO total stock holdings, among TSX/S&P and NYSE populations. In TSX/S&P population, the correlation between CEO salary and CEO total 182 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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stock holdings had increased from -.099 to .034 and then had increased further to .171, as firm size had changed from small to medium and to large. In NYSE population, the correlation between CEO salary and CEO total stocks had increased from -.162 to .111 and then had decreased to .033, as firm size had changed from small to medium and to large. In TSX/S&P population, the correlation between CEO bonus and CEO total stock holding had increased from -.14 to .155 and then had increased further to .169, as firm size had changed from small to medium and to large. Similarly, in NYSE population, the correlation between CEO bonus and CEO total stock holdings had increased from -.178 to -.155 and then had increased further to -.012, as firm size had changed from small to medium and to large. In addition, firm size had a positive influence on the correlation between CEO salary, CEO bonus, and CEO total stock holdings, among TSX/S&P and NYSE populations. Therefore, these results had indicated that there were weak mixed correlations between CEO salary, CEO bonus, and CEO total stock holdings. That is, the correlations between them were dependent on the extent of cash over stock options rewards, and design and culture of the CEO cash compensation system of a particular market. The study conducted by Jensen and Murphy (1989) found that CEO stock ownership had not played any role towards pay performance sensitivity in CEO cash compensation. This is supported by Murphy and Jensen (1990), who found that there was a small and insignificant existence of positive coefficient of CEO total stock ownership, which implied that the relation between CEO compensation and firm performance was independent of the executive’s stock holdings. The studies conducted 183 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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by Agrawal & Knoeber (1996), Himmelberg et al. (1999), and Demsetz and Villalonga (2001), all had failed to find any relationship between firm value and the executives’ equity stakes. However, Ungson and Steers (1984) found that firms where the CEO had large stock ownership, longest tenure, control of top management team or other means, a CEO can largely shape his or her pay. This was supported by Finkelstein and Hambrick (1989), who believed that executives who own significant portions of their firms are likely to control not only operating decisions but board decisions as well. Such executives would hence be in a position to essentially set their own compensation. In addition, a study conducted by Mehran (1995) found a positive relationship between percentages of total compensation in cash (salary and bonus) and percentages of shares held by managers. Overall, previous studies and this research study’s results were found to be divergent. That is, previous studies had found from nil to strong correlations between CEO compensation and CEO total stock holdings, however, this research study’s findings ranged from weak negative to weak positive ratios. In conclusion, this research study’s results had led to development of eleventh new theory: there is a weak mixed correlation between CEO salary, CEO bonus, and CEO total stock holdings. That is, the correlation will depend on board decision to reward based on extent of cash over stock options, and design and culture of CEO cash compensation system in a particular market. In addition, firm size will have a positive influence towards the correlation between CEO salary, CEO bonus, and CEO total stock holdings. 184 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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The correlation results had shown that there were mixed correlations between CEO salary, CEO bonus, and total value of CEO stocks, among TSX/S&P and NYSE populations. It had shown that in TSX/S&P population, there were positive correlations between CEO salary, CEO bonus, and CEO total value of stocks. However, in NYSE population, there were mixed correlations between CEO salary, CEO bonus, and total value of CEO stocks. In TSX/S&P population, the correlation between CEO salary and total value of CEO stocks had decreased from .218 to .031 and then had increased to .347, as firm size had changed from small to medium and to large. In NYSE population, the correlation between CEO salary and total value of CEO stocks had increased from .236 to -.041 and then had increased further to .154, as firm size had changed from small to medium to large. In TSX/S&P population, the correlation between CEO bonus and total value of CEO stocks had decreased from .215 to .106 and then had increased to .226, as firm size had changed from small to medium and to large. However, in NYSE population, the correlation between CEO bonus and total value of CEO stocks had decreased from -.134 to -.137 and then had increased to .06, as firm size had changed from small to medium and to large. In addition, the large firm size had a positive influence on the correlation between CEO salary, CEO bonus, and total value of CEO stocks, among TSX/S&P and NYSE populations. Therefore, these results had indicated that there were weak mixed correlations between CEO salary, CEO bonus, and total value of CEO stocks. That is, the nature of correlations between them was dependent on design and culture of CEO compensation of a particular market. The literature review 185 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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had indicated there was only one research study conducted on the correlation between CEO compensation and total value of CEO stocks. That is, the study conducted by Jensen and Murphy (1990), who found that, the total value of CEO stocks were immaterial towards determining CEO compensation. In conclusion, this research study’s results had led to development of twelfth new theory: there is a weak mixed correlation between CEO salary, CEO bonus, and total value of CEO stocks. The nature of the correlations was influenced by market price of the stock, and design and culture of the CEO compensation system of a particular market. In addition, the large firm size will have a positive correlation between CEO salary, CEO bonus, and total value of CEO stocks.
The correlation results had shown that there were mixed correlations between CEO salary, CEO bonus, and CEO tenure, among TSX/S&P and NYSE populations. In TSX/S&P population, the correlation between CEO salary and CEO tenure had increased from .097 to .264 and then had decreased to .210, as firm size had changed from small to medium and to large. In NYSE population, the correlation between salary and CEO tenure had increased from .074 to .232 and then had decreased to .178, as firm size had changed from small to medium and to large. In TSX/S&P population, the correlation between bonus and CEO tenure had increased from .053 to .138 and then had decreased to -.037, as firm size had changed from small to medium and to large. However, in NYSE population, it had increased from -.086 to -.064 and then had further 186 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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increased to -.019, as firm size had changed from small to medium and to large. In addition, it was found that large firm size had a mixed influence on the correlation between CEO salary, CEO bonus, and CEO tenure, among TSX/S&P and NYSE populations. The study conducted by Murphy (1986) found that CEO tenure was influenced by CEO performance-contingent pay. In addition, he believed that a long CEO tenure may promote a principal’s trust of an agent. Hermalin and Weisbach (1998), Bebchuk and Fried (2003), and Larcker and Rusticus (2004) found that CEOs over time acquire greater managerial power. Sigler (2011) argued that tenure of CEO appeared to be one of significant variables in determining the level of CEO compensation. However, Finkelstein and Hambrick (1989) stated that a monotonic relationship was not found between CEO tenure and CEO pay. Overall, previous studies and this research study had generally agreed that there was a mixed correlation between CEO compensation and CEO tenure. However, this research study was conducted based on firm size perspective, therefore, the results were more articulate. In conclusion, this research study results had led to the development of thirteenth new theory, there is a weak positive correlation between CEO salary and CEO tenure; and there is a weak mixed correlation between CEO bonus and CEO tenure, that is, the correlation between them will depend on CEO performance and board appreciation of CEO tenure. In addition, firm size will have a mixed influence on the correlation between CEO salary, CEO bonus, and CEO tenure.
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The correlation results had shown that there were mixed correlations between CEO salary, CEO bonus, and CEO turnover, among TSX/S&P and NYSE populations. In TSX/S&P population, the correlation between CEO salary and CEO turnover had decreased from -.063 to -.159 and then had increased to .105, as firm size had changed from small to medium and to large. In NYSE population, the correlation between CEO salary and CEO turnover had increased from -.132 to -.225 and then had decreased to .166, as firm size had changed from small to medium and to large. In TSX/S&P population, the correlation between CEO bonus and CEO turnover had decreased from .123 to -.088 and then had increased to -.027, as firm size had changed from small to medium and to large. Similarly, in NYSE population, the correlation between CEO bonus and CEO turnover had decreased from .09 to .02 and then had further decreased to -.002, as firm size had changed from small to medium and to large. In addition, firm size had a mixed influence on the correlation between CEO salary, CEO bonus, and CEO turnover, among TSX/S&P and NYSE populations. The study conducted by Jensen and Murphy (1990) found that CEO turnover probabilities were negatively and significantly related to changes in shareholder wealth. In addition, they concluded that the dismissals were simply not an important source of CEO incentives. Murphy and Oyer (2002) found that outside CEO replacements receive higher compensation than insider CEO replacements. That is, outside replacement CEOs, at median, typically make $335,360 more than their predecessors while insiders were typically paid only $126,156 more than their predecessors. Brickley (2003) concluded that firm 188 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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performance continues to explain very little variation of CEO turnover. Overall, previous studies and this research study results were divergent. That is, previous studies had found a positive correlation between CEO compensation and CEO turnover, however, this research study’s findings were mixed: that is, the correlation between them depended on CEO performance and the board appreciation of the length of CEO’s service. In conclusion, this research study’s results had led to the development of a fourteenth new theory: there is a weak positive correlation between CEO salary and CEO tenure, and there is a weak mixed correlation between CEO bonus and CEO tenure, that is, the correlation between them will depend on CEO performance and board appreciation of the CEO service length. In addition, the firm size will have a mixed influence on the correlation between CEO salary, CEO bonus, and CEO tenure.
The correlation results had shown that there were mixed correlations between CEO salary, CEO bonus, and 5% management ownership, among TSX/S&P and NYSE populations. In TSX/S&P population, the correlations between CEO Salary and 5% management ownership had increased from -.124 to .045 and then had decreased to .001, as firm size had changed from small to medium and to large. In NYSE population, the correlation between CEO salary and 5% management ownership had decreased from -.079 to -.238 and then had increased to -.05, as firm size had changed from small to medium and to large. In TSX/S&P population, the correlation between bonus and 5% management ownership had increased from .106 to .154 and then had decreased to 189 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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.101, as firm size had changed from small to medium and to large. In NYSE population, it had increased from -.09 to -.047 and then had increased further to .143, as firm size had changed from small to medium and to large. In addition, the large firm size had a positive influence on the correlation between CEO salary, CEO bonus, and 5% management ownership. The study conducted by Boudreaux (1973), Plamer (1973), and Gomez-Mejia, Tosi, and Hinkin (1987) found that when there was no external equity holder with at least 5% of the stock, firm is called management controlled firm. Bertrand and Mullainathan (2000) found that CEOs in firms that lacked five percent or larger stock ownership tend to receive more luck based pay, that is, pay associated with profit increases that were entirely generated by external factors rather than by managers’ efforts. In addition, they also found firms that lacked large external stakeholders; cash compensation of CEOs was reduced less when their option-based compensation was increased. Jensen and Murphy (1989) found that executive inside stock ownership could provide incentives, but these holdings were not generally controlled by corporate boards and the majority of top executives hold small personal equity ownership. Overall, previous studies and this research study’s results were found to be divergent. That is, previous studies had found a positive correlation between CEO cash compensation and 5% management ownership, whereas, this research study had found a mixed correlation between CEO cash compensation and 5% management ownership, depended on firm size and culture of the CEO compensation system of a particular market. In conclusion, this research study’s results had led to the development of a 190 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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fifteenth new theory: there is a weak mixed correlation between CEO salary, CEO bonus, and 5% management ownership, indicating the correlation between them will depend on the ownership structure, and design and culture of the CEO compensation system of a particular market. In addition, the large firm size will have a mixed influence on the correlation between CEO salary, CEO bonus, and 5% management ownership.
The correlation results had shown that there were mixed correlations between CEO salary, CEO bonus, and 5% individual/institutional ownership, among TSX/S&P and NYSE populations. In TSX/S&P population, the correlation between CEO salary and 5% individual/Institutional ownership had decreased from .309 to -.062 and then had increased to .018, as firm size had changed from small to medium and to large. In NYSE population, the correlation between CEO salary and 5% individual/institutional ownership had decreased from .096 to -.03 and then had decreased further to -.176, as firm size had changed from small to medium and to large. In TSX/S&P population, the correlation between bonus and 5% individual/institutional ownership had increased from .07 to -.18 and then had increased to -.08, as firm size had changed from small to medium and to large. However, in NYSE population, it had decreased from -.067 to .001 and then had decreased further to -.015. In addition, the large firm size had a negative influence on the correlation between CEO salary, CEO bonus, and 5% individual/institutional ownership. The study conducted by Gomez-Mejia, Tosi, and Hinkin (1987) found that executives in externally controlled firms receive more 191 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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compensation for performance and less for scale of operation than their counterparts in firms without dominant stockholders. In addition, they believed that outside dominant stockholders view firms primarily as investments and have power and incentive to align compensation of CEOs with performance of firms. Lambert et al. (1987) found a negative relation between CEO compensation and 5% of outstanding stocks, when an outside block holder owns at least 5% of outstanding stocks. This is supported by David, Kochar and Levitas (1998), who found that CEO pay was negatively correlated with presence of pressure resistant institutional investors and positively correlated with presence of pressure sensitive ones. This is also supported by Cyert, Kang and Kumar (2002), who found a negative relationship between equity ownership of largest shareholder and amount of CEO compensation. In addition, doubling the percentage ownership of the outside shareholder reduced non-salary compensation by 12-14%. That is, equity ownership of the largest external shareholder had a strong negative relation to the size of CEO equity compensation and total variable pay. Overall, previous and this research study results had agreed that there was a negative relationship between CEO cash compensation and 5% individual/institutional ownership. In conclusion, this research study results had led to the development of sixteenth and final theory, there is a weak negative correlation between CEO salary, CEO bonus, and 5% individual/Institutional ownership. In addition, the large firm size will have a negative influence on the correlation between CEO cash compensation and 5% individual/institutional ownership. 192 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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The correlation results had found that there was a relationship between CEO salary, CEO bonus, and CEO power, among TSX/S&P and NYSE indexes companies, except for the relationship between CEO bonus and CEO power in NYSE medium sized companies. Among TSX/S&P and NYSE populations, it was found that there were weak to moderate positive correlations between CEO salary and CEO age. However, among TSX/S&P and NYSE populations, it was found that there were weak negative correlations between CEO salary and CEO age. Among TSX/S&P and NYSE populations, it was found that there were weak mixed correlations between CEO salary, CEO bonus and CEO total stocks. That is, the correlation was depended on board decision to reward based on extent of cash over stock options, and design and culture of CEO cash compensation system of a particular market. In TSX/S&P population, it was found that there were positive correlations between CEO salary, CEO bonus, and CEO total value of stocks. In NYSE population, it was found that there were weak mixed correlations between CEO salary, CEO bonus, and CEO total value of stocks. That is, the nature of this correlation was depended on the market price of the stock, and design and culture of the CEO compensation system in a particular market. Among TSX/S&P and NYSE populations, it was found that there were weak positive correlations between CEO salary, CEO bonus, and CEO turnover. Among TSX/S&P and NYSE populations, it was found that there were weak negative correlations between CEO salary, CEO bonus, and CEO turnover. Among TSX/S&P and NYSE populations, it was found that there were weak mixed correlations between CEO salary, CEO bonus, and 5% 193 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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management ownership. That is, the nature and extent of correlation will be based on design and culture of the CEO compensation system in a particular market. Among TSX/S&P and NYSE populations, it was found that there were weak negative correlations between CEO salary, CEO bonus, and 5% individual/institutional ownership. The CEO total stock holdings, total value of CEO stocks, CEO tenure, and 5% management ownership had a positive firm size influence on CEO cash compensation. The CEO age, CEO turnover, and 5% individual/institutional ownership had a negative firm size influence on CEO cash compensation. Compared to previous studies, few circumstances the results were in agreement; some instances there were no previous studies to relate with; and in other cases previous results had lacked empirical results to compare clearly with these research findings.
5.4 CEO CASH COMPENSATION MODELS Based on the statistical results, there are four CEO cash compensation models have been developed among TSX/S&P and NYSE indexes companies. The purpose of these models is to demonstrate the most influential variables that affect CEO salary and bonus in TSX/S&P and NYSE indexes companies. The following figure 2 shows the CEO salary models in respective TSX/S&P and NYSE indexes companies. The TSX/S&P CEO salary model consists of: total revenues, return on equity, net profit margin, common stocks outstanding, the market value of common stocks outstanding, CEO age, CEO total value of stocks outstanding, and CEO tenure. On the other hand, 194 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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the NYSE CEO salary model consists of: total revenues, earnings per share, cash flow per share, net profit margin, common stocks outstanding, the market value of common stocks outstanding, CEO age, and CEO total value of stocks outstanding. FIGURE 5 TSX/S&P & NYSE Salary Models !
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The following Figure 6 shows the CEO bonus models in respective TSX/S&P and NYSE indexes companies. The TSX/S&P CEO bonus model consists of: total revenues, return on equity, net profit margin, common stocks outstanding, the market value of common stocks outstanding, CEO total value of stocks outstanding, and 5% management stock ownership. On the other hand, the NYSE CEO bonus model consists of: total revenues, return on assets, net profit margin, and book value of common stocks outstanding.
FIGURE 6 TSX/S&P & NYSE Bonus Models
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5.5 CHAPTER CONCLUSION The following are sixteen conclusions obtained from this research study:
1. There is a mixed correlation between CEO salary, CEO bonus, and firm size. In addition, the large firm size will have a negative impact on the correlation between them. That is, the board expected the organization to operate at optimal efficiency as such, CEO actions became less of a milestone for board to reward CEO with high cash compensation, or board selected to reward the CEO on an equity basis.
2. There is a weak positive correlation between CEO cash compensation and return on assets. In addition, the large firm size will have a mixed impact on the correlation between CEO cash compensation and return on assets.
3. There is a weak mixed correlation between CEO cash compensation and return on equity. That is, the correlation between them will depend on the importance of the return on equity on CEO performance criteria. In addition, the large firm size will have a mixed impact on the correlation between CEO cash compensation and return on equity.
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4. There is a weak mixed correlation between CEO salary, CEO bonus, and earnings per share. That is, the correlation between them will depend on the firm’s earnings and the extent of short term CEO incentives. In addition, the effect of firm size on the correlation between them will depend on design and culture of the CEO compensation system of a particular market.
5. There is a weak mixed correlation between CEO salary, CEO bonus, and cash flow per share. That is, the correlation between them will depend on the firm’s balance of operating cash flow and board decision to reward based on extent of cash over stock options. In addition, the effect of firm size on the correlation between them will depend on design and culture of the CEO compensation system of a particular market.
6. There is a positive correlation between CEO salary, CEO bonus, and net profit margin. In addition, the large firm size will have a positive influence towards the correlation between CEO salary, CEO bonus, and net profit margin.
7. There is a mixed correlation between CEO salary, CEO bonus, and common stocks outstanding. That is, the correlation between them will depend on firm’s equity position and ownership structure. In addition, the large firm size will have a
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mixed influence on the correlation between CEO cash compensation and common stocks outstanding.
8. There is a positive correlation between CEO salary, CEO bonus, and book value of common stocks outstanding. In addition, the large firm size will have a negative influence towards the correlation between CEO salary, CEO bonus, and book value of common stocks outstanding.
9. There is a mixed correlation between CEO salary, CEO bonus, and market value of common stocks outstanding. That is, the correlation between them will depend on board decision to reward based on extent of cash over stock options. In addition, the effect of firm size on the correlation between them will depend on design and culture of the CEO compensation system of a particular market.
10. There is a weak to moderate positive correlation between CEO salary and CEO age, perhaps due to experience. There is a weak positive correlation between CEO bonus and CEO age, indicating bonus is rewarded based on the firm’s performance and achievement of strategic goals. In addition, firm size will have a negative influence on the correlation between CEO salary, CEO bonus, and CEO age.
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11. There is a weak mixed correlation between CEO salary, CEO bonus, and CEO total stocks. That is, the correlation will depend on a board decision to reward based on extent of cash over stock options, and design and culture of CEO cash compensation system of a particular market. In addition, firm size will have a positive influence on the correlation between CEO salary, CEO bonus, and CEO total stock holdings.
12. There is a weak mixed correlation between CEO salary, CEO bonus, and total value of CEO stocks. That is, the nature and extent of the correlation will be influenced by market price of the stock, and design and culture of the CEO compensation system of a particular market. In addition, the large firm size will have a positive correlation between CEO salary, CEO bonus, and CEO total value of stocks.
13. There is a weak positive correlation between CEO salary and CEO tenure. There is a weak mixed correlation between CEO bonus and CEO tenure, indicating that, the correlation between them will depend on CEO performance and board appreciation of the CEO length of service. In addition, firm size will have a positive influence on the correlation between CEO salary, CEO bonus, and CEO tenure.
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14. There is a weak mixed correlation between CEO salary, CEO bonus, and CEO turnover, indicating the correlation between them will be based on firm size and external or internal recruitment of a new CEO. In addition, the large firm size will have a mixed influence on the correlation between CEO salary, CEO bonus, and CEO turnover.
15. There is a weak mixed correlation between CEO salary, CEO bonus, and 5% management ownership, indicating the correlation between them will depend on the ownership structure, and design and culture of the CEO compensation system of a particular market. In addition, the large firm size will have a mixed influence on the correlation between CEO salary, CEO bonus, and 5% management ownership.
16. There is a weak negative correlation between CEO salary, CEO bonus, and 5% individual/Institutional ownership. In addition, the large firm size will have a negative influence on the correlation between CEO cash compensation and 5% individual/institutional ownership.
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CHAPTER SIX CONCLUSION AND FUTURE STUDY
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CHAPTER 6 - CONCLUSION AND FUTURE STUDY 6.1 SUMMARY OF RESEARCH PROCESS This research study was conducted to understand the nature and extent of the relationship between CEO cash compensation, firm size, firm performance, and CEO power, among TSX/S&P and NYSE indexes companies. In addition, to clarify shareholders, investors, and the public on determinants of CEO cash compensation. That is, to explain them CEO cash compensation was not fully dependent upon accounting performance rather it involved a set of complex variables that includes firm size, firm performance, CEO power (corporate governance), and other factors such as, the achievement of strategic goals, ownership effect, market culture, and provisions of CEO contract.
This research study was based on three research questions. The first research question was, among TSX/S&P and NYSE indexes companies, what relationship is there between CEO cash compensation and firm size?. The second research question was, among TSX/S&P and NYSE indexes companies, what relationship is there between CEO cash compensation and firm performance?. The third research question was, among TSX/S&P and NYSE indexes companies, what relationship is there between CEO cash compensation and CEO power?. This research was historical and numerical 203 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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therefore, were required collecting, counting, and classifying data, and producing clear results. It also required a high level of objectivity and accuracy, and a process to include method of deductive reasoning by use of measurement tools. In addition, it required to only establish associations among variables using effect statistics such as correlations. As such, a quantitative research method was selected for this research study. The longitudinal study was selected to collect six years of data from 2005 to 2010. The stratified sample method was selected for this research study since it required equal stratum towards determining sample sizes. That is, this research study aimed to understand the effect of firm sizes on the relationship between CEO cash compensation, firm size, firm performance, and CEO power, among TSX/S&P and NYSE populations.
The total of two hundred and forty companies was selected from TSX/S&P and NYSE indexes companies. Each population had consisted of one hundred and twenty companies. Each sub population or firm size had a sample size of forty companies. The sample companies were selected from the websites Canadianbusiness.com and NYSE.com. The small size companies were selected based on total revenues of up to $500 million. The medium size companies were selected based on total revenues of over $500 million and up to $2 billion. The large size companies were selected based on total revenues of over $2 billion. These specific ranges were created to ensure
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maximum number of companies from diverse industry background were eligible for stratified sampling.
A total of thirty six statistical models was developed and tested between the subdependent variables of CEO cash compensation and the independent variables of firm size, firm performance, and CEO power, among TSX/S&P and NYSE populations, to address three research questions of this study. The sub-dependent variables of CEO cash compensation were salary and bonus. The sub-dependent variables of firm size were total sales and total employees. The sub-dependent variables of firm performance were return on equity, return on assets, earnings per share, cash flow per share, net profit margin, common stocks outstanding, book value of per common share, and market value per common stock. The sub-dependent variables of CEO power were CEO age, CEO total stock holdings, total value of CEO stocks, CEO tenure, CEO turnover, 5% management ownership, and 5% individual/institutional ownership.
The validity determined whether research truly measures what it was intended to measure or how accurate research results had been. It was based on face validity, content validity, criterion-related validity, construct validity, convergent validity, divergent validity, discriminant validity, statistical conclusion validity, and external validity. The face validity was based on designing a survey form to collect relevant data from companies for sampling. The content validity had been based on fourteen structured 205 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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quantitative questionnaires on CEO cash compensation, firm size, firm performance, and CEO power. The criterion validity was represented by firm performance, firm size, and CEO power. The construct validity was represented by sub variables of CEO cash compensation, firm performance, and CEO power. The convergent validity was assessed by reviewing t-tests for factor loadings. The divergent validity was not applicable due to survey questions were not related and opposite to each other. The discriminant validity was based on minimum and maximum values of sub variables. The statistical validity was based on correlation results among variables of CEO cash compensation, firm performance, firm size, and CEO power. In addition, a confidence interval of ninety five percent was assigned to measure the results. The external validity was based on analyses of variance and correlation results. The reliability of data was based on the assumption of repeatability. The data for this research study was directly obtained from SEDAR and EDGAR databases, which were considered highly accurate, complete, and verified.
The survey method was selected to collect historical data. The survey was designed into five sections. The first section of survey was based on company background. The second section of survey was based on company performance. The third section of survey was based on CEO remuneration. The fourth section of survey was based on CEO profile. The final and fifth section of survey was based on the firm’s ownership. The survey had consisted of fourteen structured questions. The documents that were 206 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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examined to collect corporate data comprised of annual reports, management and information circulars, audited annual financial statements, and proxies and information statements.
The data analysis for this research study was based on two phases. The first phase of data analysis was performed after the surveys were completed that includes checking for accuracy and completeness of survey forms, and data transformation from survey forms to Microsoft Excel spreadsheets and to then on the SPSS data sheets. The second phase of data analysis consisted of performing multivariate analysis in SPSS software. That is, the linear regression test was conducted to analyze data. During the first phase of data analysis, data were transferred manually from survey forms to Microsoft Excel spreadsheets for electronic recording. In the Microsoft Excel spreadsheets, columns and rows were labeled according to variables. Each model’s data were recorded on separate sheets to ensure the data were free from grouping error. Each data sheet was checked to ensure all survey questions were answered. In addition, each data sheet was checked for outliers (odd data) by observing, sorting, and analyzing marginal variances. Once they were found, they were then cross referenced to survey forms, to verify accuracy. To ensure each company consisted of six years (from 2005 to 2010) of data, “company” column was sorted by year. In addition, financial ratios were formatted to four decimal places and CEO salary and bonus information were formatted to zero decimal places, to achieve accuracy in the statistical results. The 207 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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second phase of data analysis consisted of copying and pasting data from Microsoft Excel spreadsheets to SPSS data sheets. In SPSS, data sheets were checked for accuracy and completeness by cross-referenced to Microsoft Excel data sheets. The dependent and independent variables, regression coefficients, residuals, plots, predicted values, and distances were analyzed from the linear regression test. The outliers identified through “caseware diagnostic” test were removed by deleting data rows, and accordingly retests were conducted till no outliers were found in the statistical model. The data were then analyzed in nine steps. The first step consisted of an analysis of mean and standard deviation of each variable. The second step consisted of a Pearson correlation test and test of significance. The third step consisted of regression (R2) and change statistics tests. The fourth step consisted of an analysis of variance (ANOVA) test, F-test, residual test, and p-value or confidence interval test. The fifth step consisted of an unstandardized and standardized coefficient tests, t test, and collinearity statistics test. The sixth step consisted of correlations and covariance tests. The seventh step consisted of an eigenvalue, condition index and variance proportion tests. The eighth step consisted of a predicted value, standard predicted value, Cook’s distance, and Mahal distance tests. The ninth and final step consisted of graphical tests on regression-standardized residual, scatter plot, and partial regression residual plot. After the completion of data analysis, all the model test results were saved separately in the SPSS database before they were downloaded to Microsoft Excel spreadsheets for
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the format. Once tables and graphs were formatted for size, they were copied from Microsoft Excel spreadsheets and pasted onto this research paper in Appendix D. 6.1.1 Conclusion – CEO Cash Compensation and Firm Size The results (provided in Appendix E section 1.1 to 1.12) indicated that there were relationships between CEO salary, CEO bonus, and firm size, among TSX/S&P and NYSE indexes companies, except for the relationship between CEO bonus and firm size in medium sized NYSE companies. In TSX/S&P population, model regression (R2) was ranged from weak to moderate ratios across all eight firm sizes. Similarly, in NYSE population, model regression (R2) was ranged from weak to moderate ratios across all eight firm sizes.
In the TSX/S&P population, the correlations between CEO salary, CEO bonus and total sales were ranged from moderate to good positive ratios. However, the results also indicated that firm size had a negative influence on the correlations between CEO salary, CEO bonus, and total sales. The correlations between CEO salary and total number of employees were ranged from weak negative to good positive ratios. The correlations between CEO bonus and total number of employees were ranged from weak negative to weak positive ratios. However, the results also indicated that firm size had a negative influence on the correlations between CEO salary, CEO bonus, and total number of employees. In the NYSE population, the correlations between CEO salary 209 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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and total sales were ranged from weak to good positive ratios. The correlations between CEO bonus and total sales were ranged from weak to moderate positive ratios. However, the results also indicated that firm size had a negative influence on the correlations between CEO salary, CEO bonus, and total sales. The correlations between CEO salary and total employees were ranged from weak negative to good positive ratios. The correlations between CEO bonus and total employees had weak negative to weak positive ratios. However, the results indicated firm size had a negative influence on the correlations between CEO salary, CEO bonus, and total employees. Therefore, these results had led to the development of first new theory: there is a mixed correlation between CEO salary, CEO bonus, and firm size. In addition, the large firm size will have a negative impact on the correlation between them. That is, the board expected the organization to operate at optimal efficiency as such, CEO actions became less of a milestone for board to reward CEO with high cash compensation, or board selected to reward the CEO on an equity basis. 6.1.2 Conclusion – CEO Cash Compensation and Firm Performance The results (provided in Appendix E section 2.1 to 2.12) indicated that there were relationships between CEO salary, CEO bonus, and firm performance, among TSX/S&P and NYSE indexes companies, except for the relationship between CEO bonus and firm performance in large sized NYSE companies. In TSX/S&P population, model regression
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(R2) was ranged from weak to good ratios. In NYSE population, model regression (R2) was ranged from weak to moderate ratios.
Among TSX/S&P and NYSE populations, it was found that there were mixed correlations between CEO salary, CEO bonus, and return on assets. In TSX/S&P population, it was found that there were weak correlations between CEO salary, CEO bonus, and return on equity. In NYSE population, it was found that there were mixed correlations between CEO salary, CEO bonus, and return on equity. Among TSX/S&P and NYSE populations, it was found that there were mixed correlations between CEO salary, CEO bonus, and earnings per share. Among TSX/S&P and NYSE populations, it was found that there were mixed correlations between CEO salary, CEO bonus, and cash flow per share. In TSX/S&P population, it was found that there were weak to good positive correlations between CEO salary, CEO bonus, and net profit margin. In NYSE population, it was found that there were mixed correlations between CEO salary, CEO bonus, and net profit margin. In TSX/S&P population, it was found that there were weak to moderate positive correlations between CEO salary, CEO bonus, and common stocks outstanding. In NYSE population, it was found that there were weak mixed correlations between CEO salary, CEO bonus, and common stocks outstanding. In TSX/S&P population, it was found that there were moderate to good correlations between CEO salary, CEO bonus, and book value of common stocks outstanding. In NYSE population, it was found that there were weak to moderate correlations between 211 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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CEO salary, CEO bonus, and book value of common stocks outstanding. In TSX/S&P population, it was found that there were weak to good positive correlations between CEO salary, CEO bonus, and market value of common stocks outstanding. In NYSE population, it was found that there were weak negative to weak positive correlations between CEO salary, CEO bonus, and market value of common stocks outstanding.
In addition, return on equity, earnings per share, and market value of common stocks outstanding had a mixed firm size influence on CEO cash compensation. That is, they were dependent upon the design of CEO contract and culture of a particular market. The return on assets, cash flow per share, and net profit margin had a positive firm size influence on CEO cash compensation. The common stocks outstanding and book value of common stocks outstanding had a negative firm size influence on CEO cash compensation. Overall, these results had led to the development of eight new theories:
1. There is a weak positive correlation between CEO cash compensation and return on assets. In addition, the large firm size will have a positive impact on the correlation between CEO cash compensation and return on assets.
2. There is a weak mixed correlation between CEO cash compensation and return on equity. That is, the correlation between them will depend on the importance of return on equity on CEO performance criteria. In addition, the large firm size will 212 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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have a mixed impact on the correlation between CEO cash compensation and return on equity.
3. There is a weak mixed correlation between CEO salary, CEO bonus, and earnings per share. That is, the correlation between them will depend on the firm’s earnings and extent of short-term CEO incentives. In addition, the effect of firm size on the correlation between them will depend on design and culture of the CEO compensation system of a particular market.
4. There is a weak mixed correlation between CEO cash compensation and return on equity. That is, the correlation between them will depend on the importance of return on equity on CEO performance criteria. In addition, the large firm size will have a positive impact on the correlation between CEO cash compensation and return on equity.
5. There is a positive correlation between CEO salary, CEO bonus, and net profit margin. In addition, the large firm size will have a positive influence towards the correlation between CEO salary, CEO bonus, and net profit margin.
6. There is a mixed correlation between CEO salary, CEO bonus, and common stocks outstanding. That is, the correlation between them will depend on the 213 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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firm’s equity position and ownership structure. In addition, the large firm size will have a negative influence on the correlation between CEO cash compensation and common stocks outstanding.
7. There is a positive correlation between CEO salary, CEO bonus, and book value of common stocks outstanding. In addition, the large firm size will have a mixed influence towards the correlation between CEO salary, CEO bonus, and book value of common stocks outstanding.
8. There is a mixed correlation between CEO salary, CEO bonus, and market value of common stocks outstanding. That is, the correlation between them will depend on board decision to reward based on extent of cash over stock options. In addition, the effect of firm size on the correlation between them will depend on design and culture of the CEO compensation system of a particular market. 6.1.3 Conclusion – CEO Cash Compensation and CEO Power The results (provided in Appendix E section 3.1 to 3.12) indicated that there were relationships between CEO salary, CEO bonus, and CEO power, among TSX/S&P and NYSE indexes companies, except for the relationship between CEO bonus and CEO power in small and medium sized NYSE companies. Among TSX/S&P and NYSE populations, model regression (R2) was characterized as weak ratios. 214 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Among TSX/S&P and NYSE populations, it was found that there were weak to moderate positive correlations between CEO salary and CEO age. However, among TSX/S&P and NYSE populations, it was found that there were weak negative correlations between CEO salary and CEO age. Among TSX/S&P and NYSE populations, it was found that there were weak mixed correlations between CEO salary, CEO bonus and CEO total stock holdings. That is, the correlations between them were dependent upon the board decision to reward based on extent of cash over stock options. In addition, design and culture of CEO cash compensation system of a particular market. In TSX/S&P population, it was found that there were positive correlations between CEO salary, CEO bonus, and total value of CEO stocks. In NYSE population, it was found that there were mixed correlations between CEO salary, CEO bonus, and total value of CEO stocks. That is, the correlations were dependent upon the market price of the stock, and design and culture of the CEO compensation system of a particular market. Among TSX/S&P and NYSE populations, it was found that there were weak positive correlations between CEO salary, CEO bonus, and CEO turnover. Among TSX/S&P and NYSE populations, it was found that there were weak negative correlations between CEO salary, CEO bonus, and CEO turnover. Among TSX/S&P and NYSE populations, it was found that there were weak mixed correlations between CEO salary, CEO bonus, and 5% management ownership. That is, the correlations were dependent upon ownership structure of the firm. In addition, design and culture of 215 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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the CEO compensation system of a particular market. Among TSX/S&P and NYSE populations, it was found that there were weak negative correlations between CEO salary, CEO bonus, and 5% individual/institutional ownership.
In addition, among TSX/S&P and NYSE indexes companies, CEO total stock holdings, total value of CEO stocks, CEO tenure, and 5% management ownership had a positive firm size influence on CEO cash compensation. However, among TSX/S&P and NYSE indexes companies, CEO age, CEO turnover, and 5% individual/institutional ownership had a negative firm size influence on CEO cash compensation. Overall, these results had led to the development of seven new theories:
1. There is a weak to moderate positive correlation between CEO salary and CEO age, perhaps due to experience. There is a weak positive correlation between CEO bonus and CEO age, indicating CEO bonus is rewarded based on the firm’s performance and achievement of strategic goals. In addition, firm size will have a negative influence on the correlation between CEO salary, CEO bonus, and CEO age.
2. There is a weak mixed correlation between CEO salary, CEO bonus, and CEO total stock holdings. That is, the correlation will depend on the board’s decision to reward based on extent of cash over stock options, and design and culture of 216 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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CEO cash compensation system of a particular market. In addition, firm size will have a positive influence on the correlation between CEO salary, CEO bonus, and CEO total stock holdings.
3. There is a weak mixed correlation between CEO salary, CEO bonus, and total value of CEO stocks. That is, the nature and extent of the correlation will be influenced by market price of the stock, and design and culture of the CEO compensation system of a particular market. In addition, the large firm size will have a positive correlation between CEO salary, CEO bonus, and total value of CEO stocks.
4. There is a weak positive correlation between CEO salary and CEO tenure. There is a weak mixed correlation between CEO bonus and CEO tenure, indicating the correlation between them will depend on CEO performance and board appreciation of the CEO service length. In addition, firm size will have a mixed influence on the correlation between CEO salary, CEO bonus, and CEO tenure.
5. There is a weak mixed correlation between CEO salary, CEO bonus, and CEO turnover, indicating the correlation between them will be based on firm size and external or internal recruitment of a new CEO. In addition, the large firm size will
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have a mixed influence on the correlation between CEO salary, CEO bonus, and CEO turnover.
6. There is a weak mixed correlation between CEO salary, CEO bonus, and 5% management ownership, indicating the correlation between them will depend on the ownership structure, and design and culture of the CEO compensation system of a particular market. In addition, the large firm size will have a mixed influence on the correlation between CEO salary, CEO bonus, and 5% management ownership.
7. There is a weak negative correlation between CEO salary, CEO bonus, and 5% individual/Institutional ownership. In addition, the large firm size will have a negative influence on the correlation between CEO cash compensation and 5% individual/institutional ownership.
6.2 FUTURE RESEARCH Although this research had succeeded in understanding the nature and extent of the relationship between CEO cash compensation, firm size, firm performance, and CEO power, among TSX/S&P and NYSE indexes companies, yet further studies need to be conducted to understand CEO compensation on comprehensive basis such as, to conduct research on CEO long-term compensation components (in particular pensions 218 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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and benefits) and the influence of other non-financial components such as governance (board and ownership structure). This was strongly suggested after analyzing the results of thirty six statistical models that CEO compensation system is very complex and it is influenced by firm size, ownership structure, market culture, achievements of organizational strategic goals, CEO influence on the board of directors, and design of CEO contract. Following are recommended areas for future research:
1. The nature and extent of the relationship between CEO compensation and nonfinancial performance factors in the management and owner-controlled companies from 2005 to 2013. This research will make an invaluable contribution to the executive compensation literature, the nature and extent of the influence of CEO power (in particular CEO stock ownership and CEO tenure) on CEO compensation under management and owner-controlled companies.
2. The comparative study on CEO stock-based compensation among TSX/S&P and NYSE populations from 2005 to 2013. This topic will assist in understanding the nature and extent of CEO stock-based compensation (stock options) in respective markets. That is, this research will demonstrate the proportion of short and long-term compensations relative to total compensation in respective markets. Furthermore, it will demonstrate the effect of respective market culture on CEO compensation system. 219 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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3. The nature and extent of influence of CEO/Chairman dual role of CEO compensation in management and owner-controlled companies from 2005 to 2013. This research will make an invaluable contribution to executive compensation literature in understanding the duality role power on CEO compensation under management and owner-controlled companies.
4. Study on the Chinese owned public companies CEO compensation system in North America. This research will assist in understanding the nature and extent of CEO compensation of growing Chinese owned public companies listed in North American stock exchanges. It will demonstrate the effect of Chinese corporate culture and the factors that are influential in determining CEO compensation.
5. The impact of International Financial Reporting Standard (IFRS) on Canadian CEO compensation system. This research will make an invaluable contribution to Canadian executive compensation literature towards understanding the nature and extent of influence of IFRS on CEO compensation. In addition, it can also be used as a proxy towards similar studies in the United States when it adopts IFRS for corporate reporting.
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6. CEO gender and CEO compensation among TSX/S&P and NYSE indexes companies. This research will assist in understanding the nature and extent of the influence of gender on CEO compensation. Also, it will demonstrate how the respective market's culture treats gender in CEO compensation.
7. The composition of the board in determining CEO compensation from 2005 to 2013. This research will make an invaluable contribution to executive compensation literature, to understand the nature and extent of influence of board composition on CEO compensation. That is, to understand the effect of board composition and the particular group dominance, comprised of outside board members and company’s senior management personnel, on CEO compensation.
8. The ownership structure and CEO compensation from 2005 to 2013, a comparative study among TSX/S&P and NYSE indexes companies. This research will make an invaluable contribution to executive compensation literature, to understand the nature and extent of management and institutional/individual-controlled companies on CEO compensation system. Also, it will reveal the role of respective market’s ownership culture on CEO compensation.
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9. CEO compensation system in non-profit organizations. This research will assist in understanding the CEO compensation structure and the factors that influence CEO compensation system in non-profit organizations.
10. The influence of managerial power on CEO compensation. This research will make an invaluable contribution to understand the nature and extent of CEO power on compensation. It will reveal the CEO power factors that influence CEO compensation.
6.3 FINAL SUMMARY This research was conducted to understand the nature and effect of firm size, firm performance, and CEO power on CEO cash compensation, among TSX/S&P and NYSE indexes companies. In addition, to clarify concerns expressed by shareholders, investors, and the public on rewarding CEOs with salaries and bonuses. Accordingly, results of this study found that:
1. There was a relationship between CEO cash compensation, firm performance, firm size, and CEO power, among TSX/S&P and NYSE indexes companies, except for, the relationship between CEO bonus and firm size in the NYSE medium sized companies; the relationship between CEO bonus and firm 222 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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performance in the NYSE large sized companies; and the relationship between CEO bonus and CEO power in the medium sized companies.
2. The correlations among sub variables of CEO cash compensation and firm size were ranged from weak negative to good positive ratios, among TSX/S&P and NYSE indexes companies.
3. The correlations among sub variables of CEO cash compensation and firm performance were ranged from weak negative to good positive ratios, among TSX/S&P and NYSE indexes companies.
4. The correlations among sub variables of CEO cash compensation and CEO power were ranged from moderate negative to good positive ratios, among TSX/S&P and NYSE indexes companies.
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BIBLIOGRAPHIC REVIEW
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Year 1959 1960 1963 1968 1969 1971 1973 1974 1975 1976 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993
Publication 1 1 1 1 1 1 2 4 2 1 2 4 9 2 5 6 11 6 11 8 7 7 6 6 11
1994 9 1995 10
Bibliography Reference Number 214 46 251 178 45 229 31 & 204 5, 47, 210, & 230. 184 & 199. 158 134 & 146. 48, 89, 116, & 218. 4, 28, 49, 51, 53, 172, 196, 211, 214, & 216. 162 & 180. 29, 79, 99, 127, 128, & 159. 82, 90, 133, 173, 213, & 244. 6, 58, 69, 79, 80, 84, 137, 153, 160, 194, & 250. 7, 93, 149, 195, 218, & 244. 9, 31, 67, 83, 117, 121, 153, 167, 178, & 202. 11, 42, 68, 85, 189, 193, 203, & 241. 86, 118, 120, 175, 197, 239, & 258. 50, 75, 77, 108, 155, 156, & 168. 10, 44, 74, 88, 140, & 224. 119, 120, 122, 187, 206, & 226. 23, 32, 103, 106, 109, 111, 113, 161, 182, 207, & 229. 30, 35, 65, 81, 101, 123, 164, 165, & 235. 35, 105, 132, 134, 145, 147, 183, 188, 246, & 248.
249 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Year 1996 1997 1998 1999 2000
Publication 9 9 10 10 12
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
4 9 6 5 11 7 7 6 4 6 4 3 2
Bibliography Reference Number 2, 17, 40, 62, 108, 139, 192, 201, & 227. 45, 64, 116, 126, 150, 169, 205, & 209. 10, 63, 78, 102, 104, 125, 212, 219, 221, 238 & 249. 3, 25, 57, 72, 92, 101, 141, 185, & 196. 12, 70, 112, 142, 152, 166, 170, 233, 237, 245, 252, & 260. 27, 51, 70, & 210. 13, 18, 43, 59, 151, 163, 176, 190, & 198. 19, 24, 26, 37, 55, & 60. 1, 8, 20, 186, & 200. 15, 21, 22, 36, 54, 73, 111, 131, 138, 148, & 236. 52, 56, 91, 94, 176, 243, & 254. 61, 71, 72, 115, 247, 253, & 257. 70,129, 135, 143, 231, & 256. 99, 130, 171, & 232. 82, 100, 157, 220, 222, & 261. 14, 34, 181, & 225. 191, 223, & 259. 228 & 240.
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APPENDICES
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APPENDIX A: DEFINITIONS Term
Measurement
ANOVA
It is the initial step in identifying factors that are influencing a
(Analysis of
given data set. It is used to determine impact of independent
Variance)
variables have on the dependent variable in a regression analysis.
Basic Pay
Annual salary divided by base pay
Book value of
Total common stockholders' equity divided by total common
common shares
stocks outstanding.
outstanding Cash bonus
Annual performance cash bonus.
Cash flow per share
Total operating cash flow divided by total common shares outstanding.
CEO age
Age of CEO.
CEO power
Comprised of CEO age, CEO total stock holdings, total value of CEO stocks, 5% management ownership, 5% individual/institutional ownership, CEO turnover, and CEO tenure.
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Term
Measurement
CEO share value
Market price of stock times CEO stocks outstanding.
CEO stock ownership
CEO total stocks, CEO’s immediate beneficially stocks, and trust stocks over which CEO’s have a sale or shared power to direct voting.
CEO tenure
Number of years CEO is employed in the company.
CEO turnover
A change of CEO in a given year, due to direct firing, planned retirement or normal succession or promotion from CEO to Chairman.
Chairman/CEO duality
A person assumed roles of Chairman and CEO of the
role
company in a same period.
Chi-square test
It is a statistical method to test whether two or more variables are independent or homogeneous.
Coefficient
A number or symbol multiplied with a variable or an unknown quantity in the regression equation.
Collinearity/Multi-
When a regressor is nearly a linear combination of other
Collinearity
regressors in the model, affected estimates are unstable and have high standard errors.
Common stocks
The shares of a corporation's stock that have been issued
outstanding
and are in the hands of the public.
Condition index
It is calculated as: scale columns of the X matrix to have unit sums of squares, and then calculate singular values of scale X matrix and square them. If the condition index is 15, multicollinearity is a concern, and if it is greater than 30 multicollinearity is a very serious concern.
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Term
Measurement
Control variable
A variable which held constant to assess the relationship between two other variables.
Cook's distance
It measures the effect of deleting a given observation.
Correlation
A mutual relationship or connection between two or more variables.
Correlation
It measures the degree to which two variables are linearly
coefficient
related. The ratio falls between -1 and 1.
Deductive approach
It is a logical process in which conclusion is drawn from a set of premises contains no more information than premises taken collectively.
Degree of freedom
A number of independent observations in a sample minus the number of population parameters that must be estimated from sample data.
Dependent variable
A variable whose value depends on that of another.
Descriptive statistics
Presentation of data in the form of tables and charts or summarized by means of percentiles and standard deviations.
Dummy variable
The modify the form of non numeric variables by assigning one or two digit numeric coding to allow their effects to be included in the regression model.
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Term
Measurement
Durbin Watson test
A number which determines whether there is autocorrelation in the residuals of a time series regression. The statistic ranges from 0 to 4 with 0 indicating positive autocorrelation and 4 indicating negative correlation. A value of 2 indicates no auto correlation in the sample.
Earnings per share
Net profits divided by total common stocks outstanding.
Eigenvalue
The non-zero vectors or values that after being multiplied by the matrix, remain parallel to original vector or value. The first factor will always account for the most variance (and hence have the highest eigenvalue), and the next and subsequent factors will account for less and less variance. Eigenvalues close to zero indicate a multicollinearity problem.
Firm performance
Comprised of return on total assets, return on total equity, earnings per share, cash flow per share, and net profit margin.
Firm size
Comprised of total sales, total assets, and number of employees.
F-test
It is designed to test if two population variances are equal. It does this by comparing the ratio of two variances. So, if the variances are equal, the ratio of the variances will be 1.
Heteroscedasticity
An irregular scattering of values in a series of distributions accompanied by a comparable scatter of variances.
Histogram
A graphical representation showing a visual impression of the distribution of data.
Homogenous
Essentially alike.
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Term
Measurement
Homoscedasticity
All random variables in the sequence or vector have the same finite variance.
Independent
A variable whose value does not depend on that of another.
variable Inductive approach
It is a process of transforming reasoning from detailed facts to general principles.
Inferential statistics
A process of drawing information from sampled observations of a population and making conclusions about the population.
Linear Regression
A technique in which a straight line is fitted to a set of data points to measure the effect of a single independent variable.
Longitudinal study
A study that involves the repeated observation or examination of a set of subjects over time with respect to one or more study variables.
Mahal distance
It is based on correlations between variables by which different patterns can be identified and analyzed.
Management
Management team owns a majority or at least fifty percent of
controlled
company stock.
Market value of
Market price of stock times total common stocks outstanding.
common stocks outstanding Mean
Mathematical average of a set of numbers.
Net profit margin
Net profits divided by total sales.
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Term
Measurement
Non parametric
Data plot makes no assumption about characteristics of data.
testing Number of
Total employees in a company.
employees Owner controlled
Individuals or institutional own majority or at least fifty percent of company stock.
Parametric testing
It assumes that the variables that are testing or comparing are distributed normally. It consists of t-test, paired t-test, Chisquare, 1-way ANOVA, Pearson’s r, and factorial ANOVA.
Partial regression
It attempts to show the effect of adding an additional variable
plot
to the model.
Partial order
It formalizes and generalizes the intuitive concept of an ordering, sequencing, or arrangement of elements of a set.
Phenomenological
It is a philosophical approach which emphasizes subjectivity
method
and research is exploratory in nature. It is often concerned with single samples and with the generation of exploratory theories. The end product of phenomenological research could be an entirely new and ground breaking theory that is then put forward for subsequent positivist testing.
Positivist method
It is a philosophical approach which emphasizes observable facts and excludes metaphysical speculation about ultimate causes.
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Term
Measurement
Qualitative
It is a research method which aims to gather an in-depth
methodology
understanding through investigations of the why and how of decision making.
Quantitative
It is a research method which follows a systematic empirical
methodology
investigation through statistical techniques.
Regression (R2)
A regression is a statistical analysis assessing the association between two variables. It is used to find the relationship between two variables.
Residual
The difference between an actual, observed value and a value predicted by a regression.
Residual Statistics
It represents unexplained (or residual) variation after fitting a regression model.
Return on total assets
Net Income divided by Total Assets.
(ROA) Return on total equity
Net Income divided by Total Equity.
(ROE) Scatter plot
The data are displayed as a collection of points, one variable determining position on the horizontal axis and other variable determining position on the vertical axis.
Significance (p-value)
The level of marginal significance within a statistical hypothesis test representing the probability of occurrence of a given event. This research has limits a p-value to .05
Standard Deviation
It shows how much variation exists from average mean.
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Term
Measurement
Standardized
It refers to how many standard deviations a dependent
coefficient (Beta)
variable will change per standard deviation increase in the predictor variable.
Stratified sampling
A method of sampling that involves the division of a population into smaller groups known as strata.
Sum of squares
The sum of squares is a mathematical approach to determining the dispersion of data points.
Tolerance
1 minus squared multiple correlation of variable with all other
(confidence)
independent variables in regression equation. Maximum tolerance level for this research study is 95%.
Total assets
The sum of current and long term assets.
Total sales
Total earnings for the year.
T-test
A statistical test involving confidence limits for random variable t of a t distribution. It is used in testing hypotheses about means of normal distributions when standard deviations are unknown.
Unstandardized
The effect of an independent variable on the dependent
coefficient (Beta)
variable, net of the effects of other independent variables. It is calculated from raw or unstandardized data.
Variance proportion
A group of independent observations by number of observations in the group that represent one of two outcomes.
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Term
Measurement
Variance Inflation
It provides an index that measures how much variance
Factor (VIF)
(square of the estimate's standard deviation) of an estimated regression coefficient is increased because of collinearity. If VIF for one of the variables is around or greater than 5, there is collinearity associated with that variable. If there are two or more variables that will have a VIF around or greater than 5, one of these variables must be removed from the regression model.
Zero order
A device which converts a sampled output into an output which is held constant between the samples at the last sampled value.
Z test
A statistical test used to determine whether two population means are different when variances are known and sample size is large.
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APPENDIX B: COMPANY NAMES TSX/S&P COMPANIES SMALL
MEDIUM
LARGE
1
Abington Resources Ltd.
1
Aastra Technologies Ltd.
1
Agrium Inc.
2
Agrico-Eagle Mines Ltd
2
AGF Management Inc.
2
Air Canada
3
Akita Drilling Ltd.
3
CAE Inc.
3
Alimentation Couche-Tard Inc.
4
Alamos Gold Inc.
4
Canaccord Financial Inc.
4
Bank of Montreal
5
Algonquin Power & Utilities
5
Canada Bread Company
5
Bank of Nova Scotia
Corp. 6
Atlantis Systems Corp.
6
Canadian Western Bank
6
Barrick Gold
7
Aurizon Mines Ltd.
7
CCL Industries
7
Bombardier Inc.
8
Birchcliff Energy Ltd.
8
Centerra Gold Inc.
8
Cameco Corporation
9
Celtic Exploration Ltd.
9
Corus Entertainment
9
Canada Utilities Ltd.
10
Compton Petroleum Corp.
10
Cott Corp.
10
Canadian Imperial Bank of Commerce
11
Connacher Oil and Gas
11
Dundeewealth Inc.
11
Canadian Tire Corp.
Ltd. 12
Crew Energy Inc.
12
Emera Inc.
12
E-L Financial Corp.
13
Eldorado Gold Corp.
13
Enerflex Ltd.
13
Empire Company Ltd.
14
Equitable Group
14
Ensign Energy Services Inc.
14
Finnning International
15
European Goldfield Ltd.
15
First Quantum Minerals Ltd.
15
Goldcorp Inc.
16
Exco Technologies Ltd.
16
Flint Energy Services Ltd.
16
Husky Energy
17
Fairborne Energy Ltd.
17
Garda World Security Corp.
17
IGM Financial Inc.
18
Glacier Media Inc.
18
Gildan Activewear Inc.
18
Laurentian Bank of Canada
19
GMP Capital Inc.
19
Groupe Aeroplan
19
Loblaw Companies Ltd.
20
Gold Star Resources Ltd.
20
Hudbay Minerals Inc.
20
Magna International Inc.
21
Grand Power Logistic
21
IAMGOLD Corp.
21
Manulife Financial Corp.
Group Inc. 22
Grear Basin Gold Inc.
22
Indigo Books & Music Inc.
22
Metro Inc.
23
Home Capital Group Inc.
23
Inmet Mining
23
National Bank of Canada
24
Jaguar Mining Inc.
24
Kinross Gold Corp.
24
Nexen Inc.
25
McGrawHill Ryerson Ltd.
25
Labrador Iron Ore Royalty
25
Power Corporation Canada
Corp.
261 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
TSX/S&P COMPANIES SMALL
MEDIUM
LARGE
26
New Gold Inc.
26
Lundin Mining Corp.
26
Power Financial Corp.
27
Niko Resources Ltd.
27
Methenex Corp.
27
Research In Motion Ltd.
28
Pacific & Western Credit
28
Mullen Group Ltd.
28
Rogers Communications Inc.
Corp. 29
Pan Orient Energy Corp.
29
New Flyer Industries Inc.
29
RONA Inc.
30
Petrolifera Petroleum Ltd.
30
North American Energy
30
Royal Bank of Canada
Partners Inc. 31
Pure Technologies Ltd.
31
Petrobank Energy Inc.
31
Saputo Inc.
32
Silver Wheaton Corp.
32
Reitmans (Canada) Ltd.
32
Sears Canada Inc.
33
Thompson Creek Metals Inc.
33
Shawcor Ltd.
33
Shaw Communications Inc.
34
Transglobe Energy Corp.
34
Sheritt International
34
Shoppers Drug Mart Corp.
35
Tucows Inc.
35
Torstar Corp.
35
Sunco Energy
36
TVA Group Inc.
36
Transforce Inc.
36
Teck Resources
37
Uranium One
37
Uni-Select Inc.
37
Tim Hortons
38
Velan Inc.
38
Valeant Pharmaceutical
38
Transat AT Inc.
International Inc. 39
Vero Energy
39
Yamana Gold Inc.
39
Transcontinental Inc.
40
Western Coal Corp.
40
Yellow Media Inc.
40
WestJet Airlines Ltd.
262 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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NYSE COMPANIES SMALL 1
MEDIUM
Acadia Realty Trust
1
Advance American Cash
LARGE 1
Advanced Micro Devices Inc.
2
Agilent Technologies Inc.
Advance 2
Aetna Inc.
2
Alliance Data System Corp.
3
Agree Realty Corp.
3
American Greetings Corps.
3
Allergan Inc.
4
Align Technologies Inc.
4
American Reprographics
4
Alliance Healthcare Services
5
Alliance Health Care Inc.
5
American Tower Corp.
5
American International Inc.
6
American Oriental
6
Astoria Financial Corp.
6
Anadarks Petroleum Corp.
Bioengineering Inc. 7
Amrep Corp.
7
Bank of Hawaii Corp.
7
Analog Devices Inc.
8
Atlantic Power Corporation
8
BankCorp South Inc.
8
Bank of America Corp.
9
BankAtlantic Bancorp Inc.
9
Bio Rad Laboratories
9
Barter International Inc.
10
Callon Petroleum
10
Callaway Golf
10
Becton Dickinson & Co.
11
Carbo Ceramics
11
Camden Property Trust
11
Boston Scientific Corp.
12
Central Pacific Financial
12
CBIZ Inc.
12
Bristol Myers Squible Co.
Corp 13
Cryolife Inc.
13
Cenveo Inc.
13
Chesapeake Energy Corp.
14
Darling International Inc.
14
CIBER Inc.
14
Chevron Energy
15
DuCommun Inc.
15
Cincinnati Bell Inc.
15
Chiquite Brand Int. Inc.
16
Emulex Corp.
16
City National Corp.
16
Citigroup Inc.
17
Enzo Biochem Inc.
17
Core Laboratories
17
Claiborne Liz Inc.
18
Fabrinet Corp.
18
Crawford & Company
18
Clorox Co.
19
First acceptance Corp.
19
Doral Financial Corp.
19
CNQ Financial Group Inc.
20
First Commonwealth
20
Edwards Lifesciences
20
Comstock Resources Inc.
Financial Corp.
Corp.
21
Flotek Industries Inc.
21
Ensco plc.
21
ConocoPhillips Inc.
22
Frontline Ltd.
22
Equifax Inc.
22
Dean Foods Company
23
GMX Resources Inc.
23
Exco Resources Inc.
23
Devon Energy Corp.
263 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
NYSE COMPANIES SMALL
MEDIUM
LARGE
24
GP Strategic Corp.
24
Federa Signal Corp.
24
Diamond Offshore Drilling Inc.
25
Grey Television Inc.
25
Five Star Quality Care
25
Dynergy Inc.
26
Harvest Natural Resources
26
Forest Oil Corp
26
EMC Corp.
27
Furniture Brands International
27
Fedex
28
First American Financial
Inc. 27
Ion Geophyscial Corp.
Inc. 28
Journal Communications
28
Gartner Inc.
Inc.
Corp.
29
Kid Brands Inc.
29
IDT Corp.
29
GenOn Energy
30
Kodiak Oil & Gas Corp.
30
Imitation Corp.
30
Hartford Financial Services Inc.
31
Metropolitan Health
31
Intermec Inc.
31
IBM Corp
Networks Inc. 32
Omega Protein Corp.
32
Key Energy Services Inc.
32
JP Morgan Chase & Co.
33
One Liberty Properties Inc.
33
Knight Transportation Inc.
33
KB Home
34
Oriental Financial Group Inc.
34
Meadowbrook Insurance
34
NRG Energy Inc.
Group Inc. 35
Par Technology Corp.
35
Navigant Consulting Inc.
35
NV Energy Inc.
36
Saga Communications Inc.
36
NCI Building Systems Inc.
36
Pitney Bowes Inc.
37
Schiff Nutrition International
37
Primus Telecommunications
37
Teco Energy Inc.
Inc. 38
Symmetry Medical Inc.
38
Quantum Corp.
38
Tenet Healthcare Corp.
39
Theragenics Corp.
39
Sunrise Senior Living Inc.
39
Thompson Reuters Corp.
40
Tyler Technologies Inc.
40
Zebra Technologies Corp.
40
Xeros Inc.
264 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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APPENDIX C: SURVEY QUESTIONS I. Background 1. Please specify the industry your company associated with: 0 Aerospace & Defense 1 Agriculture 2 Automotive 3 Biotech 4 Building & Construction 5 Business Services 6 Chemicals 7 Consumer Products 8 Energy 9 Engineering 10 Financial Services 11 Funds 12 Healthcare 13 Industrials 14 Leisure & Entertainment 15 Metal & Mining 16 Paper & Packaging 17 Publishing & Media 18 Real Estate 19 Technology 20 Telecommunications 21 Transportations
265 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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2. Average number of employees in each period:
2005: __________________ 2006: __________________ 2007: __________________ 2008: __________________ 2009: __________________ 2010: __________________
II. Firm Performance 1. Please state following firm performances for each period:
Total Sales (1)
Return on Total Assets (2)
Return on Equity (3)
2005: ____________
____________
____________
2006: ____________
____________
____________
2007: ____________
____________
____________
2008: ____________
____________
____________
2009: ____________
____________
____________
2010: ____________
____________
____________ 266
Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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2. Please state following per share information for each period:
Earnings Per share (1)
Cash Flow per share (2)
Net Profit Margin (3)
2005: __________________
__________________
__________________
2006: __________________
__________________
__________________
2007: __________________
__________________
__________________
2008: __________________
__________________
__________________
2009: __________________
__________________
__________________
2010: __________________
__________________
__________________
267 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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III. Remuneration 1. Please list CEO salary and cash bonus earned for following periods (at each fiscal year-end):
Basic Salary (1) Cash Bonus (2) Total Cash Compensation (3) Total Compensation (4)
2005: __________ ____________ _____________________
________________
2006: __________ ____________ _____________________
________________
2007: __________ ____________ _____________________
________________
2008: __________ ____________ _____________________
________________
2009: __________ ____________ _____________________
________________
2010: __________ ____________ _____________________
________________
268 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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IV. CEO Profile 1. Please select CEO gender:
0Male
1Female
2. Please select CEO age group: 0 1 2 3 4
CEO age less than 50 CEO age between 51 and 55 CEO age between 56 and 60 CEO age between 61 and 65 CEO age 66 or greater
3. Please state number of years CEO is with the organization: __________.
4. Please state how many times, if any, CEO turnover happened from 2005 to 2010: ________.
269 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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V. Firm Performance 1. Please select ownership class of your company:
0 Owner-managed (stock ownership is concentrated among individual/institutional investors) 1 Management-controlled (stock ownership is dispersed among firm’s executives/managers)
2. Please state how many management individuals within the firm owns five percent or more of the company’s stock?
Management individuals (0)
2005: __________________ 2006: __________________ 2007: __________________ 2008: __________________ 2009: __________________ 2010: __________________
270 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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3. Please state how many individuals or institutional investors own five percent or more of the company’s stock?
Individual/Institutional investors (0)
2005: __________________ 2006: __________________ 2007: __________________ 2008: __________________ 2009: __________________ 2010: __________________
271 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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4. How many stocks CEO, CEO closed family, and CEO connected trust owned during each period (at fiscal year-end), excluding stock options?
Total CEO stock (0)
CEO total value of stocks (1)
2005: __________________
__________________
2006: __________________
__________________
2007: __________________
__________________
2008: __________________
__________________
2009: __________________
__________________
2010: __________________
__________________
5. Total shareholder wealth outstanding (at fiscal year-end):
Common stocks outstanding (0) Book value (1)
Market value (2)
2005: __________________
__________________
__________________
2006: __________________
__________________
__________________
2007: __________________
__________________
__________________
2008: __________________
__________________
__________________
2009: __________________
__________________
__________________
2010: __________________
__________________
__________________ 272
Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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APPENDIX D: DATA RESULTS SECTION 1.1: TSX/S&P SMALL SIZE COMPANIES (SALARY VS. SALES & EMPLOYEES)
Descriptive Statistics Std. Mean
Deviation
N
SALARY
366,658
175,761
239
TOTAL SALES
183,375,551
186,298,691
239
NO. OF
590
829
239
EMPLOYEES
Correlations TOTAL
NO. OF
SALARY
SALES
EMPLOYEES
Pearson
SALARY
1.000
.574
.540
Correlation
TOTAL SALES
.574
1.000
.500
NO. OF
.540
.500
1.000
SALARY
.
.000
.000
TOTAL SALES
.000
.
.000
NO. OF
.000
.000
.
SALARY
239
239
239
TOTAL SALES
239
239
239
NO. OF
239
239
239
EMPLOYEES Sig. (1-tailed)
EMPLOYEES N
EMPLOYEES
273 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Model Summary
b
Mode
Change Statistics
l
R
1
R
Adjuste
Squar
dR
R
e
.644
.415
Square
F
Std. Error of the
Chang
Chang
df
Square
Estimate
e
e
1
.410
134974.887090
.415
83.784
2
a
4
Sig. F
Durbin-
Chang
Watso
df2
e
n
23
.000
.743
6
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: SALARY
ANOVA
b
Model 1
Sum of Squares
df
Mean Square
F
Sig.
Regression
3052784214730.310
2
1526392107365.150
83.784
.000
Residual
4299499954236.160
236
18218220145.069
Total
7352284168966.470
238
a
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: SALARY
Coefficients
a
Model Unstandardized
Standardized
Coefficients
Coefficients
B
Std. Error
(Constant)
254295.606
12461.889
TOTAL
.000
.000
71.578
12.194
t
Sig.
20.406
.000
.405
7.052
.000
.337
5.870
.000
Beta
SALES NO. OF EMPLOYEES a. Dependent Variable: SALARY
274 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Coefficients
a
Model 95.0% Confidence Interval for B
Correlations
Lower
Upper
Bound
Bound
(Constant)
229744.851
278846.362
TOTAL
.000 47.554
Collinearity Statistics
Zero-order
Partial
Part
Tolerance
VIF
.000
.574
.417
.351
.750
1.334
95.602
.540
.357
.292
.750
1.334
SALES NO. OF EMPLOYEES a. Dependent Variable: SALARY
Coefficient Correlations
a
Model 1
Correlations
NO. OF
NO. OF
TOTAL
EMPLOYEES
SALES
1.000
-.500
-.500
1.000
148.701
.000
.000
.000
EMPLOYEES TOTAL SALES Covariances
NO. OF EMPLOYEES TOTAL SALES
a. Dependent Variable: SALARY
275 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Collinearity Diagnostics Model
1
a
Dimension
Eigenvalue
Condition
Variance Proportions
Index
(Constant)
TOTAL
NO. OF
SALES
EMPLOYEES
1
2.322
1.000
.07
.06
.07
2
.419
2.353
.57
.00
.60
3
.259
2.996
.36
.94
.33
a. Dependent Variable: SALARY
276 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
254725.078125
1140725.625000
366658.426778
113255.5713051
239
-.988
6.835
.000
1.000
239
8778.153
61389.070
13603.268
6619.292
239
256910.578125
1125266.125000
366685.573138
112874.5372700
239
Residual
-325874.2187500
361978.6250000
.0000000
134406.5692522
239
Std.
-2.414
2.682
.000
.996
239
-2.429
2.751
.000
1.003
239
-329854.9062500
381165.7187500
-27.1463599
136280.4248187
239
-2.455
2.791
.001
1.007
239
.011
48.237
1.992
4.668
239
.000
.135
.005
.014
239
.000
.203
.008
.020
239
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value
Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: SALARY
277 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
278 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
279 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
280 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
281 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
282 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 1.2 TSX/S&P SMALL SIZE COMPANIES (BONUS VS. SALES & EMPLOYEES)
Descriptive Statistics Mean
Std. Deviation
N
BONUS
172,481
189140.8455176
219
TOTAL
163,163,857
161226280.7264480
219
555
758.189
219
SALES NO. OF EMPLOYEES
Correlations TOTAL
NO. OF
BONUS
SALES
EMPLOYEES
Pearson
BONUS
1.000
.358
.125
Correlation
TOTAL
.358
1.000
.394
.125
.394
1.000
SALES NO. OF EMPLOYEES Sig. (1-
BONUS
.
.000
.032
tailed)
TOTAL
.000
.
.000
.032
.000
.
BONUS
219
219
219
TOTAL
219
219
219
219
219
219
SALES NO. OF EMPLOYEES N
SALES NO. OF EMPLOYEES
283 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Model Summary Mode
R
l
b
R
Adjuste
Std. Error of the
Change
Durbin
Squar
dR
Estimate
Statistic
-
e
Square
s
Watso n
1
.359
.129
.121
a
177369.216886
R
F
df
Square
Chang
1
Change
e
.129
15.948
df2
Sig. F Chang e
2
9
21
.000
6
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: BONUS ANOVA
b
Model 1
Sum of Squares
df
Mean Square
F
Sig.
Regression
1003463313199.360
2
501731656599.680
15.948
.000
Residual
6795325245395.990
216
31459839099.056
Total
7798788558595.350
218
a
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: BONUS
284 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
1.374
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
5.964
.000
B
Std. Error
Beta
(Constant)
105100.840
17621.652
TOTAL
.000
.000
.366
5.294
.000
-4.736
17.235
-.019
-.275
.784
SALES NO. OF EMPLOYEES a. Dependent Variable: BONUS Coefficients Model
95.0% Confidence Interval for
Collinearity
B
Correlations
Lower
Upper
Bound
Bound
(Constant)
70368.431
139833.248
TOTAL
.000
-38.706
Statistics
Zero-order
Partial
Part
Tolerance
VIF
.001
.358
.339
.336
.845
1.183
29.234
.125
-.019
-
.845
1.183
SALES NO. OF EMPLOYEES
.017
a. Dependent Variable: BONUS
285 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Coefficient Correlations
a
Model 1
Correlations
NO. OF
NO. OF
TOTAL
EMPLOYEES
SALES
1.000
-.394
-.394
1.000
297.045
-.001
-.001
.000
EMPLOYEES TOTAL SALES Covariances
NO. OF EMPLOYEES TOTAL SALES
a. Dependent Variable: BONUS Collinearity Diagnostics Model
a
Dimension
1
Eigenvalue
Condition
Variance Proportions
Index
(Constant)
TOTAL
NO. OF
SALES
EMPLOYEES
1
2.300
1.000
.07
.06
.07
2
.420
2.341
.33
.05
.85
3
.281
2.863
.60
.89
.07
a. Dependent Variable: BONUS
286 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
90921.914063
535725.750000
172480.579909
67845.7273607
219
-1.202
5.354
.000
1.000
219
12027.197
68821.273
18821.501
8778.364
219
74931.828125
550413.687500
172400.689900
68089.9749855
219
Residual
-430823.3750000
505957.9375000
.0000000
176553.7219149
219
Std. Residual
-2.429
2.853
.000
.995
219
Stud.
-2.584
2.958
.000
1.008
219
-487600.6875000
553195.6875000
79.8900089
181113.5628341
219
-2.619
3.013
.003
1.015
219
.007
31.825
1.991
4.100
219
.000
.379
.009
.040
219
.000
.146
.009
.019
219
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value
Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: BONUS
287 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
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288 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
289 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
290 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
291 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
292 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
293 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 1.3 NYSE SMALL SIZE COMPANIES (SALARY VS. SALES & EMPLOYEES) Descriptive Statistics Mean
Std. Deviation
N
SALARY
366476
176108.8772382
238
TOTAL
183842650
186551013.3823260
238
592
829.698
238
SALES NO. OF EMPLOYEES Correlations SALARY
TOTAL
NO. OF
SALES
EMPLOYEES
Pearson
SALARY
1.000
.575
.542
Correlation
TOTAL
.575
1.000
.500
.542
.500
1.000
SALES NO. OF EMPLOYEES Sig. (1-
SALARY
.
.000
.000
tailed)
TOTAL
.000
.
.000
.000
.000
.
SALARY
238
238
238
TOTAL
238
238
238
238
238
238
SALES NO. OF EMPLOYEES N
SALES NO. OF EMPLOYEES
294 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model Summary Model
R
b
R
Adjusted
Std. Error of the
Change Statistics
Square
R
Estimate
R
F
Square
Change
Square
Durbindf1
df2
Sig. F
Watson
Change
Change 1
.646
a
.417
.412
135018.1191793
.417
84.103
2
235
.000
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: SALARY ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
3066373045095.040
2
1533186522547.520
84.103
.000
Residual
4284024739078.700
235
18229892506.718
Total
7350397784173.730
237
a
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: SALARY Coefficients
a
Model
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
20.269
.000
B
Std. Error
Beta
(Constant)
253412.649
12502.663
TOTAL
.000
.000
.406
7.067
.000
71.869
12.202
.339
5.890
.000
SALES NO. OF EMPLOYEES a. Dependent Variable: SALARY
295 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
.746
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
95.0%
Correlations
Collinearity
Confidence
Statistics
Interval for B Lower
Upper
Zero-order
Partial
Part
Tolerance
VIF
Bound
Bound
(Constant)
228781.027
278044.271
TOTAL SALES
.000
.000
.575
.419
.352
.750
1.333
NO. OF
47.829
95.909
.542
.359
.293
.750
1.333
EMPLOYEES a. Dependent Variable: SALARY Coefficient Correlations
a
Model 1
Correlations
NO. OF
NO. OF
TOTAL
EMPLOYEES
SALES
1.000
-.500
-.500
1.000
148.896
.000
.000
.000
EMPLOYEES TOTAL SALES Covariances
NO. OF EMPLOYEES TOTAL SALES
a. Dependent Variable: SALARY
296 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics Model
1
Dimension
a
Eigenvalue
Condition
Variance Proportions
Index
(Constant)
TOTAL
NO. OF
SALES
EMPLOYEES
1
2.323
1.000
.07
.06
.07
2
.418
2.356
.57
.00
.61
3
.259
2.997
.36
.94
.33
a. Dependent Variable: SALARY
297 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
253843.859375
1142701.500000
366476.319328
113746.5730943
238
-.990
6.824
.000
1.000
238
8797.597
61446.172
13640.268
6626.927
238
256034.765625
1127734.500000
366506.683319
113382.6513825
238
Residual
-325780.1250000
362446.7812500
.0000000
134447.2154839
238
Std.
-2.413
2.684
.000
.996
238
-2.428
2.750
.000
1.003
238
-329759.8750000
381073.5312500
-30.3639908
136325.0896527
238
-2.453
2.789
.001
1.007
238
.010
48.090
1.992
4.659
238
.000
.135
.005
.014
238
.000
.203
.008
.020
238
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value
Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: SALARY
298 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
299 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
300 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
301 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
302 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
303 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 1.4 NYSE SMALL SIZE COMPANIES (BONUS VS. SALES & EMPLOYEES)
Descriptive Statistics Mean BONUS TOTAL
Std. Deviation
N
171712.14
189233.198
218
162006415.63
160682797.867
218
551.59
757.900
218
SALES NUMBER OF EMPLOYEES Correlations BONUS
TOTAL
NUMBER OF
SALES
EMPLOYEES
Pearson
BONUS
1.000
.355
.121
Correlation
TOTAL
.355
1.000
.389
.121
.389
1.000
.
.000
.037
.000
.
.000
.037
.000
.
BONUS
218
218
218
TOTAL
218
218
218
218
218
218
SALES NUMBER OF EMPLOYEES Sig. (1-
BONUS
tailed)
TOTAL SALES NUMBER OF EMPLOYEES
N
SALES NUMBER OF EMPLOYEES
304 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model Summary Model
R
b
R
Adjusted
Std. Error
Change Statistics
Square
R
of the
R
F
Square
Estimate
Square
Change
Durbindf1
df2
Sig. F
Watson
Change
Change 1
.126
.355
.118
177728.198
.126
15.502
2
215
.000
a. Predictors: (Constant), NUMBER OF EMPLOYEES, TOTAL SALES b. Dependent Variable: BONUS ANOVA
b
Model
Sum of Squares
df
Mean Square
F
1 Regression
979324890943.882
2
489662445471.941
Residual
6791272183304.710
215
31587312480.487
Total
7770597074248.590
217
Sig.
15.502
.000
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: BONUS Coefficients
a
Model
Unstandardized
Standardized
Coefficients
Coefficients
B (Constant) TOTAL
Std. Error
t
Sig.
5.961
.000
Beta
105327.866
17668.688
.000
.000
.362
5.234
.000
-4.948
17.280
-.020
-.286
.775
SALES NUMBER OF EMPLOYEES a. Dependent Variable: BONUS
305 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
1.375
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
95.0%
Correlations
Collinearity
Confidence
Statistics
Interval for B
(Constant)
Lower
Upper
Bound
Bound
Zero-order
Partial
Part
Tolerance
VIF
70501.838
140153.895
.000
.001
.355
.336
.334
.849
1.178
-39.008
29.112
.121
-.020
-
.849
1.178
TOTAL SALES NUMBER OF
.018
EMPLOYEES a. Dependent Variable: BONUS Coefficient Correlations
a
Model 1
Correlations
NUMBER OF
NUMBER OF
TOTAL
EMPLOYEES
SALES
1.000
-.389
-.389
1.000
298.598
-.001
-.001
.000
EMPLOYEES TOTAL SALES Covariances
NUMBER OF EMPLOYEES TOTAL SALES
a. Dependent Variable: BONUS
306 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics Model
1
Dimension
a
Eigenvalue
Condition
Variance Proportions
Index
(Constant)
TOTAL
NUMBER OF
SALES
EMPLOYEES
1
2.295
1.000
.07
.06
.08
2
.423
2.329
.32
.05
.86
3
.282
2.851
.61
.88
.07
a. Dependent Variable: BONUS
307 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Minimum
Maximum
Mean
Std.
N
Deviation Predicted
90441.90
533308.19
171712.14
67178.999
218
-1.210
5.383
.000
1.000
218
12072.374
69290.023
18881.436
8862.247
218
74390.27
548580.69
171625.97
67413.961
218
-428624.125
506326.063
.000
176907.278
218
-2.412
2.849
.000
.995
218
-2.567
2.962
.000
1.008
218
-485767.688
555254.875
86.173
181521.894
218
-2.602
3.017
.003
1.015
218
.006
31.987
1.991
4.126
218
.000
.387
.009
.040
218
.000
.147
.009
.019
218
Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual Std. Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: BONUS
308 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
309 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
310 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
311 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
312 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 1.5 TSX/S&P MEDIUM SIZE COMPANIES (SALARY VS. SALES & EMPLOYEES)
Descriptive Statistics Mean
Std. Deviation
N
SALARY
611146.06
234372.892
234
TOTAL
1051002911.94
560547251.140
234
5290.10
6893.046
234
SALES NUMBER OF EMPLOYEES Correlations SALARY
TOTAL
NUMBER OF
SALES
EMPLOYEES
Pearson
SALARY
1.000
.477
.029
Correlation
TOTAL
.477
1.000
.144
.029
.144
1.000
SALES NUMBER OF EMPLOYEES Sig.
SALARY
.
.000
.329
(1-tailed)
TOTAL
.000
.
.014
.329
.014
.
SALARY
234
234
234
TOTAL
234
234
234
234
234
234
SALES NUMBER OF EMPLOYEES N
SALES NUMBER OF EMPLOYEES
313 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model Summary Model
R
b
R
Adjusted
Std. Error
Change Statistics
Square
R Square
of the
R
F
Estimate
Square
Change
Durbindf1
df2
Sig. F
Watson
Change
Change 1
.479
a
.229
.222
206681.645
.229
34.309
2
231
.000
.605
a. Predictors: (Constant), NUMBER OF EMPLOYEES, TOTAL SALES b. Dependent Variable: SALARY ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
2931145204794.250
2
1465572602397.120
34.309
.000
Residual
9867696804619.800
231
42717302184.501
Total
12798842009414.100
233
a
a. Predictors: (Constant), NUMBER OF EMPLOYEES, TOTAL SALES b. Dependent Variable: SALARY Coefficients
a
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
13.747
.000
B
Std. Error
Beta
(Constant)
406275.430
29554.515
TOTAL
.000
.000
.483
8.268
.000
-1.368
1.985
-.040
-.689
.491
SALES NUMBER OF EMPLOYEES a. Dependent Variable: SALARY
314 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Coefficients 95.0%
Correlations
Collinearity
Confidence
Statistics
Interval for B Lower
Upper
Zero-order
Partial
Part
Tolerance
VIF
Bound
Bound
(Constant)
348044.563
464506.296
TOTAL SALES
.000
.000
.477
.478
.478
.979
1.021
NUMBER OF
-5.279
2.542
.029
-.045
-.040
.979
1.021
NUMBER OF
TOTAL
EMPLOYEES
SALES
1.000
-.144
-.144
1.000
3.940
.000
.000
.000
EMPLOYEES a. Dependent Variable: SALARY Coefficient Correlations
a
Model 1
Correlations
NUMBER OF EMPLOYEES TOTAL SALES
Covariances
NUMBER OF EMPLOYEES TOTAL SALES
a. Dependent Variable: SALARY
315 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
316 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
317 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
318 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
319 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
320 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 1.6 TSX/S&P MEDIUM SIZE COMPANIES (BONUS VS. SALES & EMPLOYEES) Descriptive Statistics Mean
Std. Deviation
N
BONUS
693815.07
621483.685
229
TOTAL
1047933560.68
562592654.701
229
5347.56
6950.697
229
SALES NUMBER OF EMPLOYEES
Correlations TOTAL
NUMBER OF
BONUS
SALES
EMPLOYEES
Pearson
BONUS
1.000
.250
-.019
Correlation
TOTAL
.250
1.000
.144
-.019
.144
1.000
SALES NUMBER OF EMPLOYEES Sig. (1-
BONUS
.
.000
.390
tailed)
TOTAL
.000
.
.015
.390
.015
.
BONUS
229
229
229
TOTAL
229
229
229
229
229
229
SALES NUMBER OF EMPLOYEES N
SALES NUMBER OF EMPLOYEES
321 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model Summary
b
Model
Change Statistics
R 1
.256
a
Adjusted
Std. Error
R
R
R
of the
Square
F
Square
Square
Estimate
Change
Change
df1
.065
.057
603439.929
.065
7.919
2
Sig. F
Durbin-
df2
Change
Watson
226
.000
1.133
a. Predictors: (Constant), NUMBER OF EMPLOYEES, TOTAL SALES b. Dependent Variable: BONUS
ANOVA
b
Model 1
Sum of Squares
df
Mean Square
F
Sig.
Regression
5767586384680.610
2
2883793192340.300
7.919
.000
Residual
82295582990792.200
226
364139747746.868
Total
88063169375472.800
228
a
a. Predictors: (Constant), NUMBER OF EMPLOYEES, TOTAL SALES b. Dependent Variable: BONUS
322 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
4.858
.000
B
Std. Error
Beta
(Constant)
421853.430
86845.076
TOTAL
.000
.000
.258
3.969
.000
-4.976
5.810
-.056
-.856
.393
SALES NUMBER OF EMPLOYEES a. Dependent Variable: BONUS Coefficients
a
Model
95.0% Confidence
Collinearity
Interval for B
Correlations
Statistics
Upper Lower Bound
Bound
(Constant)
250723.797
592983.062
TOTAL
.000 -16.424
Zero-order
Partial
Part
Tolerance
VIF
.000
.250
.255
.255
.979
1.021
6.473
-.019
-.057
-
.979
1.021
SALES NUMBER OF EMPLOYEES
.055
a. Dependent Variable: BONUS
323 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model 1
Correlations
NUMBER OF
NUMBER OF
TOTAL
EMPLOYEES
SALES
1.000
-.144
-.144
1.000
33.754
.000
.000
.000
EMPLOYEES TOTAL SALES Covariances
NUMBER OF EMPLOYEES TOTAL SALES
a. Dependent Variable: BONUS
Collinearity Diagnostics Model
a
Dimension
Variance Proportions Condition
1
TOTAL
NUMBER OF
Eigenvalue
Index
(Constant)
SALES
EMPLOYEES
1
2.399
1.000
.03
.03
.07
2
.483
2.228
.05
.07
.93
3
.118
4.506
.92
.90
.00
a. Dependent Variable: BONUS
324 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Std. Minimum
Maximum
Mean
Deviation
N
367657.28
1242151.88
693815.07
159048.519
229
-2.051
3.448
.000
1.000
229
39895.133
267450.125
61973.018
30558.346
229
347528.31
1152036.13
694278.31
157283.820
229
-
1731199.000
.000
600787.433
229
-1.518
2.869
.000
.996
229
-1.528
2.877
.000
1.001
229
Deleted
-
1741313.500
-463.240
607996.810
229
Residual
927979.125
Stud.
-1.532
2.925
.002
1.006
229
.001
43.791
1.991
5.076
229
.000
.128
.004
.011
229
.000
.192
.009
.022
229
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
915948.000 Std. Residual Stud. Residual
Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: BONUS
325 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
326 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
327 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
328 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
329 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
330 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 1.7 NYSE MEDIUM SIZE COMPANIES (SALARY VS. SALES & EMPLOYEES)
Descriptive Statistics Mean
Std. Deviation
N
SALARY
692990.25
200551.166
235
TOTAL
1063855188.94
493300570.550
235
5708.10
6750.855
235
SALES NUMBER OF EMPLOYEES Correlations SALARY
TOTAL
NUMBER OF
SALES
EMPLOYEES
Pearson
SALARY
1.000
.107
-.208
Correlation
TOTAL
.107
1.000
.365
-.208
.365
1.000
SALES NUMBER OF EMPLOYEES Sig.
SALARY
.
.051
.001
(1-tailed)
TOTAL
.051
.
.000
.001
.000
.
SALARY
235
235
235
TOTAL
235
235
235
235
235
235
SALES NUMBER OF EMPLOYEES N
SALES NUMBER OF EMPLOYEES
331 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model Summary
b
Model
R
Adjusted
Std. Error
Change Statistics
Square
R Square
of the
R
F
Estimate
Square
Change
R
Durbindf1
df2
Sig. F
Watson
Change
Change 1
.286
a
.082
.074
192995.999
.082
10.340
2
232
.000
1.130
a. Predictors: (Constant), NUMBER OF EMPLOYEES, TOTAL SALES b. Dependent Variable: SALARY ANOVA
b
Model 1
Sum of Squares
df
Mean Square
F
Sig.
Regression
770250532666.164
2
385125266333.082
10.340
.000
Residual
8641409694301.520
232
37247455578.886
Total
9411660226967.680
234
a
a. Predictors: (Constant), NUMBER OF EMPLOYEES, TOTAL SALES b. Dependent Variable: SALARY Coefficients
a
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
21.673
.000
B
Std. Error
Beta
(Constant)
650002.668
29990.672
TOTAL
.000
.000
.211
3.124
.002
-8.466
2.008
-.285
-4.217
.000
SALES NUMBER OF EMPLOYEES a. Dependent Variable: SALARY
332 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Coefficients 95.0%
Correlations
Collinearity
Confidence
Statistics
Interval for B Lower
Upper
Zero-order
Partial
Part
Tolerance
VIF
Bound
Bound
(Constant)
348044.563
464506.296
TOTAL SALES
.000
.000
.477
.478
.478
.979
1.021
NUMBER OF
-5.279
2.542
.029
-.045
-.040
.979
1.021
NUMBER OF
TOTAL
EMPLOYEES
SALES
1.000
-.365
-.365
1.000
4.030
.000
.000
.000
EMPLOYEES a. Dependent Variable: SALARY Coefficient Correlations
a
Model 1
Correlations
NUMBER OF EMPLOYEES TOTAL SALES
Covariances
NUMBER OF EMPLOYEES TOTAL SALES
a. Dependent Variable: SALARY
333 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics Model
a
Dimension
1
Eigenvalue
Condition
Variance Proportions
Index
(Constant)
TOTAL
NUMBER OF
SALES
EMPLOYEES
1
2.511
1.000
.02
.02
.06
2
.400
2.504
.09
.03
.89
3
.088
5.328
.88
.94
.05
a. Dependent Variable: SALARY
334 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Minimum
Maximum
Mean
Std.
N
Deviation Predicted
438475.97
825254.50
692990.25
57373.068
235
-4.436
2.305
.000
1.000
235
12608.483
67133.688
19838.027
9072.063
235
433601.03
827440.13
692980.02
58117.013
235
Residual
-505486.813
571025.750
.000
192169.460
235
Std.
-2.619
2.959
.000
.996
235
-2.626
2.969
.000
1.002
235
-508204.125
575059.000
10.230
194505.637
235
-2.660
3.021
.000
1.007
235
.003
27.318
1.991
3.917
235
.000
.049
.004
.007
235
.000
.117
.009
.017
235
Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value
Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: SALARY
335 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
336 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
337 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
338 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 1.8 NYSE MEDIUM SIZE COMPANIES (BONUS VS. SALES & EMPLOYEES) Descriptive Statistics Mean BONUS TOTAL
Std. Deviation
N
302547.52
387850.861
234
1074487236.75
500143580.845
234
5645.55
6539.612
234
SALES NO. OF EMPLOYEES
Correlations TOTAL
NO. OF
BONUS
SALES
EMPLOYEES
1.000
.121
.027
Pearson
BONUS
Correlation
TOTAL SALES
.121
1.000
.362
NO. OF
.027
.362
1.000
.
.032
.341
EMPLOYEES Sig. (1-
BONUS
tailed)
TOTAL SALES
.032
.
.000
NO. OF
.341
.000
.
BONUS
234
234
234
TOTAL SALES
234
234
234
NO. OF
234
234
234
EMPLOYEES N
EMPLOYEES
339 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model Summary
b
Mode
Change Statistics
l
R R .122
1
a
R
Adjusted
Std. Error of
Square
F
df
df
Sig. F
Durbin-
Square
R Square
the Estimate
Change
Change
1
2
Change
Watson
.006
386593.445
.015
.015
1.759
2
23
.175
1
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: BONUS
ANOVA
b
Model 1
Sum of Squares
df
Mean Square
525804002859.434
2
262902001429.717
Residual
34523987633670.800
231
149454491920.653
Total
35049791636530.300
233
Regression
F
Sig.
1.759
.175
a
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: BONUS
340 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
1.126
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Unstandardized
Standardized
Coefficients
Coefficients
B
Std. Error
(Constant)
202267.404
60038.304
.000
.000
-1.156
4.155
TOTAL
t
Sig.
Beta 3.369
.001
.128
1.830
.069
-.019
-.278
.781
SALES NO. OF EMPLOYEES a. Dependent Variable: BONUS Coefficients
a
Model
95.0% Confidence Interval for
Collinearity
B
(Constant) TOTAL
Correlations
Lower
Upper
Bound
Bound
Zero-order
Statistics Partial
Part
.119
.869
1.151
-
.869
1.151
83974.735
320560.073
.000
.000
.121
.120
-9.342
7.029
.027
-.018
Tolerance
VIF
SALES NO. OF
.018
EMPLOYEES a. Dependent Variable: BONUS
341 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model 1
NO. OF
Correlations
EMPLOYEES
TOTAL SALES
1.000
-.362
TOTAL SALES
-.362
1.000
NO. OF
17.261
.000
.000
.000
NO. OF EMPLOYEES
Covariances
EMPLOYEES TOTAL SALES a. Dependent Variable: BONUS Collinearity Diagnosticsa Model
Dimension
Variance Proportions Condition
1
TOTAL
NO. OF
Eigenvalue
Index
(Constant)
SALES
EMPLOYEES
1
2.519
1.000
.02
.02
.06
2
.392
2.535
.09
.04
.89
3
.089
5.310
.88
.94
.05
a. Dependent Variable: BONUS
342 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Std. Minimum
Maximum
Mean
Deviation
N
203386.70
470957.53
302547.52
47504.416
234
-2.087
3.545
.000
1.000
234
25291.457
139461.391
39837.559
18178.678
234
199500.84
492559.75
302357.50
48326.171
234
-421070.281
1081953.625
.000
384930.670
234
Std. Residual
-1.089
2.799
.000
.996
234
Stud. Residual
-1.108
2.807
.000
1.002
234
-435526.188
1088064.875
190.022
390030.991
234
-1.108
2.850
.002
1.006
234
Mahal. Distance
.002
29.326
1.991
4.048
234
Cook's Distance
.000
.077
.004
.009
234
Centered Leverage
.000
.126
.009
.017
234
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
Deleted Residual Stud. Deleted Residual
Value a. Dependent Variable: BONUS
343 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
344 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
345 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
346 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
347 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 1.9 TSX LARGE SIZE COMPANIES (SALARY VS. SALES & EMPLOYEES) Descriptive Statistics Mean
Std. Deviation
N
SALARY
951849.42
426832.239
233
TOTAL SALES
10190698824.03
9417712759.890
233
NO. OF
24983.45
28549.408
233
EMPLOYEES
Correlations TOTAL
NO. OF
SALARY
SALES
EMPLOYEES
Pearson
SALARY
1.000
.297
-.083
Correlation
TOTAL
.297
1.000
.568
-.083
.568
1.000
SALARY
.
.000
.104
TOTAL
.000
.
.000
.104
.000
.
SALARY
233
233
233
TOTAL
233
233
233
233
233
233
SALES NO. OF EMPLOYEES Sig. (1-tailed)
SALES NO. OF EMPLOYEES N
SALES NO. OF EMPLOYEES
348 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model Summary
b
Model
Change Statistics Adjusted R 1
.426
a
R
R
R
Std. Error of
Square
F
Square
Square
the Estimate
Change
Change
df1
.182
.174
387821.832
.182
25.510
2
Sig. F
Durbin-
df2
Change
Watson
230
.000
.663
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: SALARY
ANOVA
b
Model 1
Sum of Squares
df
Mean Square
F
Sig.
Regression
7673768414864.130
2
3836884207432.060
25.510
.000
Residual
34593327891282.700
230
150405773440.359
Total
42267096306146.800
232
a
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: SALARY
Coefficients
a
Model
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
22.331
.000
B
Std. Error
Beta
(Constant)
856034.742
38333.723
TOTAL
.000
.000
.508
7.006
.000
-5.554
1.084
-.371
-5.125
.000
SALES NO. OF EMPLOYEES a. Dependent Variable: SALARY
349 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
95.0% Confidence Interval for
Collinearity
B
Statistics
Correlations
Lower
Upper
Bound
Bound
(Constant)
780504.589
931564.895
TOTAL
.000 -7.689
Zero-order
Partial
Part
Tolerance
VIF
.000
.297
.419
.418
.677
1.477
-3.419
-.083
-.320
-
.677
1.477
SALES NO. OF EMPLOYEES
.306
a. Dependent Variable: SALARY
Coefficient Correlations
a
Model 1
Correlations
NO. OF
TOTAL
EMPLOYEES
SALES
1.000
-.568
TOTAL SALES
-.568
1.000
NO. OF
1.175
.000
.000
.000
NO. OF EMPLOYEES
Covariances
EMPLOYEES TOTAL SALES a. Dependent Variable: SALARY
350 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics Model
a
Dimension
Variance Proportions Condition
1
TOTAL
NO. OF
Eigenvalue
Index
(Constant)
SALES
EMPLOYEES
1
2.447
1.000
.06
.04
.05
2
.344
2.666
.76
.02
.43
3
.209
3.423
.18
.94
.52
a. Dependent Variable: SALARY
351 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Std. Minimum
Maximum
Mean
Deviation
N
737227.06
2192714.00
951849.42
181869.701
233
-1.180
6.823
.000
1.000
233
25412.750
176635.500
39646.603
19138.283
233
703932.31
2200281.75
952317.00
184533.292
233
Residual
-945598.000
1134272.875
.000
386146.568
233
Std.
-2.438
2.925
.000
.996
233
-2.450
2.945
-.001
1.002
233
-954826.875
1149738.500
-467.577
391440.079
233
-2.477
2.995
.000
1.008
233
.000
47.130
1.991
4.362
233
.000
.063
.005
.009
233
.000
.203
.009
.019
233
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value
Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: SALARY
352 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
353 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
354 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
355 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 1.10 TSX LARGE SIZE COMPANIES (BONUS VS. SALES & EMPLOYEES) Descriptive Statistics Mean
Std. Deviation
N
BONUS
1154061.72
952761.497
220
TOTAL SALES
10804289959.09
10531918723.838
220
NO. OF
24717.80
27934.523
220
EMPLOYEES
Correlations TOTAL
NO. OF
BONUS
SALES
EMPLOYEES
Pearson
BONUS
1.000
.320
.112
Correlation
TOTAL
.320
1.000
.519
.112
.519
1.000
BONUS
.
.000
.048
TOTAL
.000
.
.000
.048
.000
.
BONUS
220
220
220
TOTAL
220
220
220
220
220
220
SALES NO. OF EMPLOYEES Sig. (1-tailed)
SALES NO. OF EMPLOYEES N
SALES NO. OF EMPLOYEES
356 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model Summary
b
Model
Change Statistics Adjusted R 1
.326
a
R
R
R
Std. Error of
Square
F
Square
Square
the Estimate
Change
Change
df1
.106
.098
904999.214
.106
12.863
2
Sig. F
Durbin-
df2
Change
Watson
217
.000
1.209
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: BONUS
ANOVA
b
Model 1
Sum of Squares
df
Mean Square
F
Sig.
Regression
21070112791707.000
2
10535056395853.500
12.863
.000
Residual
177728116355721.000
217
819023577676.135
Total
198798229147428.000
219
a
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: BONUS
357 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
9.512
.000
B
Std. Error
Beta
(Constant)
866312.541
91074.523
TOTAL SALES
.000
.000
.357
4.760
.000
NO. OF
-2.492
2.561
-.073
-.973
.332
EMPLOYEES a. Dependent Variable: BONUS Coefficients
a
Model
95.0% Confidence Interval for
Collinearity
B
Correlations
Lower
Upper
Bound
Bound
(Constant)
686808.637
1045816.445
TOTAL
.000 -7.540
Statistics
Zero-order
Partial
Part
Tolerance
VIF
.000
.320
.307
.306
.731
1.369
2.556
.112
-.066
-
.731
1.369
SALES NO. OF EMPLOYEES
.062
a. Dependent Variable: BONUS
358 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model 1
Correlations
NO. OF
TOTAL
EMPLOYEES
SALES
1.000
-.519
TOTAL SALES
-.519
1.000
NO. OF
6.559
.000
.000
.000
NO. OF EMPLOYEES
Covariances
EMPLOYEES TOTAL SALES a. Dependent Variable: BONUS
Collinearity Diagnostics Model
a
Dimension
Variance Proportions Condition
1
TOTAL
NO. OF
Eigenvalue
Index
(Constant)
SALES
EMPLOYEES
1
2.418
1.000
.06
.05
.06
2
.339
2.669
.79
.02
.46
3
.242
3.160
.15
.93
.48
a. Dependent Variable: BONUS
359 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Std.
Predicted
Minimum
Maximum
Mean
Deviation
N
873328.13
2853468.50
1154061.72
310178.272
220
-.905
5.479
.000
1.000
220
61063.441
363459.688
95265.381
45853.764
220
876958.31
3185170.00
1156386.84
322301.286
220
-
2617103.250
.000
900857.320
220
Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
1993428.500 Std. Residual
-2.203
2.892
.000
.995
220
Stud.
-2.379
2.948
-.001
1.007
220
Deleted
-
2720415.750
-2325.123
921536.399
220
Residual
2325130.000
Stud. Deleted
-2.405
3.002
.000
1.012
220
.002
34.328
1.991
4.211
220
.000
.314
.008
.026
220
.000
.157
.009
.019
220
Residual
Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: BONUS
360 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
361 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
362 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
363 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 1.11 NYSE LARGE SIZE COMPANIES (SALARY VS. SALES & EMPLOYEES) Descriptive Statistics Mean
Std. Deviation
N
SALARY
1029423.89
322793.986
232
TOTAL SALES
25223926534.48
48078909793.649
232
NO. OF
51788.79
91693.802
232
EMPLOYEES
Correlations TOTAL
NO. OF
SALARY
SALES
EMPLOYEES
Pearson
SALARY
1.000
.422
.407
Correlation
TOTAL
.422
1.000
.418
.407
.418
1.000
SALARY
.
.000
.000
TOTAL
.000
.
.000
.000
.000
.
SALARY
232
232
232
TOTAL
232
232
232
232
232
232
SALES NO. OF EMPLOYEES Sig. (1-tailed)
SALES NO. OF EMPLOYEES N
SALES NO. OF EMPLOYEES
364 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model Summary
b
Model
Change Statistics Adjusted R
1
.492
a
R
R
R
Std. Error of
Square
F
Square
Square
the Estimate
Change
Change
df1
.243
.236
282162.262
.243
36.659
2
Sig. F
Durbin-
df2
Change
Watson
229
.000
.807
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: SALARY ANOVA
b
Model 1
Sum of Squares
df
Mean Square
F
Sig.
Regression
5837307084567.380
2
2918653542283.690
36.659
.000
Residual
18231959096610.900
229
79615541906.598
Total
24069266181178.300
231
a
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: SALARY
Coefficients Model
a
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
365 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
B
Std. Error
(Constant)
926812.533
22088.020
TOTAL SALES
.000
.000
NO. OF
.981
.223
Beta 41.960
.000
.306
4.832
.000
.279
4.401
.000
EMPLOYEES a. Dependent Variable: SALARY Coefficients
a
Model
95.0% Confidence
Collinearity
Interval for B
Statistics
Correlations
Lower
Upper
Bound
Bound
(Constant)
883290.801
970334.265
TOTAL SALES
.000
NO. OF
.542
Zero-order
Partial
Part
Tolerance
VIF
.000
.422
.304
.278
.825
1.212
1.420
.407
.279
.253
.825
1.212
EMPLOYEES a. Dependent Variable: SALARY Coefficient Correlations
a
Model 1
NO. OF Correlations
EMPLOYEES
TOTAL SALES
1.000
-.418
TOTAL SALES
-.418
1.000
NO. OF
.050
.000
.000
.000
NO. OF EMPLOYEES
Covariances
EMPLOYEES TOTAL SALES a. Dependent Variable: SALARY
Collinearity Diagnostics
a
Model
Eigenvalue
Dimension
Variance Proportions
366 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Condition 1
TOTAL
NO. OF
Index
(Constant)
SALES
EMPLOYEES
1
2.007
1.000
.11
.11
.11
2
.547
1.916
.86
.30
.09
3
.446
2.121
.03
.59
.80
Std. Deviation
N
a. Dependent Variable: SALARY
Residuals Statistics
a
Minimum
Maximum
Mean
367 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
927468.38
1586957.75
1029423.89
158964.548
232
-.641
3.507
.000
1.000
232
18745.938
105588.742
27376.419
16770.668
232
929972.56
1675912.13
1029545.42
159409.399
232
774936.063 -2.746
619605.500
.000
280938.125
232
Std. 2.196 Residual Stud. -2.877 2.202 Residual Deleted 623076.313 Residual 875495.125 Stud. -2.924 2.221 Deleted Residual Mahal. .024 31.352 Distance Cook's .000 .449 Distance Centered .000 .136 Leverage Value a. Dependent Variable: SALARY
.000
.996
232
.000
1.003
232
-121.524
285480.500
232
-.001
1.008
232
1.991
4.835
232
.006
.030
232
.009
.021
232
368 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
369 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
370 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
371 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 1.12 NYSE LARGE SIZE COMPANIES (BONUS VS. SALES & EMPLOYEES) Descriptive Statistics Mean
Std. Deviation
N
BONUS
660847.55
966660.139
221
TOTAL SALES
23440182466.06
47116918923.112
221
NO. OF
47787.67
88063.120
221
EMPLOYEES
Correlations TOTAL
NO. OF
BONUS
SALES
EMPLOYEES
Pearson
BONUS
1.000
.090
-.150
Correlation
TOTAL
.090
1.000
.387
-.150
.387
1.000
BONUS
.
.090
.013
TOTAL
.090
.
.000
.013
.000
.
BONUS
221
221
221
TOTAL
221
221
221
221
221
221
SALES NO. OF EMPLOYEES Sig. (1-tailed)
SALES NO. OF EMPLOYEES N
SALES NO. OF EMPLOYEES
372 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model Summary
b
Model
Change Statistics Adjusted R 1
.220
a
R
R
R
Std. Error of
Square
F
Square
Square
the Estimate
Change
Change
df1
.049
.040
947235.063
.049
5.558
2
Sig. F
Durbin-
df2
Change
Watson
218
.004
1.179
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: BONUS
ANOVA
b
Model 1
Sum of Squares
df
Mean Square
F
Sig.
Regression
9973571290787.870
2
4986785645393.940
5.558
.004
Residual
195601429867521.000
218
897254265447.346
Total
205575001158309.000
220
a
a. Predictors: (Constant), NO. OF EMPLOYEES, TOTAL SALES b. Dependent Variable: BONUS
373 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
9.188
.000
B
Std. Error
Beta
(Constant)
691052.482
75212.218
TOTAL SALES
.000
.000
.175
2.440
.015
NO. OF
-2.391
.787
-.218
-3.040
.003
EMPLOYEES a. Dependent Variable: BONUS Coefficients
a
Model
95.0% Confidence Interval for
Collinearity
B
Statistics
Correlations
Lower
Upper
Bound
Bound
(Constant)
542816.300
839288.664
TOTAL
.000 -3.942
Zero-order
Partial
Part
Tolerance
VIF
.000
.090
.163
.161
.850
1.177
-.841
-.150
-.202
-
.850
1.177
SALES NO. OF EMPLOYEES
.201
a. Dependent Variable: BONUS
374 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model 1
Correlations
NO. OF
NO. OF
TOTAL
EMPLOYEES
SALES
1.000
-.387
-.387
1.000
.619
.000
.000
.000
EMPLOYEES TOTAL SALES Covariances
NO. OF EMPLOYEES TOTAL SALES
a. Dependent Variable: BONUS
Collinearity Diagnostics Model
a
Dimension
Variance Proportions Condition
1
TOTAL
NO. OF
Eigenvalue
Index
(Constant)
SALES
EMPLOYEES
1
1.962
1.000
.12
.12
.12
2
.560
1.871
.83
.37
.06
3
.478
2.026
.06
.52
.82
a. Dependent Variable: BONUS
375 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Std. Minimum
Maximum
Mean
Deviation
N
-60055.51
1510076.00
660847.55
212918.799
221
-3.386
3.989
.000
1.000
221
64132.680
366911.219
92942.789
59646.107
221
-67193.42
1715764.50
660558.26
215781.365
221
Residual
-1495947.375
2494044.000
.000
942919.619
221
Std.
-1.579
2.633
.000
.995
221
-1.691
2.679
.000
1.005
221
-1715764.500
2581545.750
289.294
961086.101
221
-1.699
2.718
.003
1.010
221
.013
32.013
1.991
5.119
221
.000
.223
.007
.026
221
.000
.146
.009
.023
221
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value
Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: BONUS
376 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
377 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
378 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
379 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 2.1 TSX SMALL (SALARY VS. ROA, ROE, EPS, CFPS, NPM, CSO, BVCSO, MVCSO) Descriptive Statistics Mean
Std. Deviation
N
SALARY
366658.426778
175761.0602203
239
ROA
-.017720
.2140611
239
ROE
-.053239
.5888933
239
EPS
.020912
4.7021806
239
CFPS
-7.075512
121.1146607
239
NPM
6992549.351464
172452406.7841680
239
CSO
104790429.669456
121773899.4304760
239
BVCSO
381090631.740586
683070387.6664510
239
MVCSO
1085973433.854230
1967855512.9320000
239
Model Summary
b
Model
Change Statistics Adjusted R
1
.695
a
R
R
R
Std. Error of the
Square
F
Square
Square
Estimate
Change
Change
df1
.483
.465
128539.2223140
.483
26.874
8
Sig. F
Durbin-
df2
Change
Watson
230
.000
.843
a. Predictors: (Constant), MVCSO, CFPS, EPS, ROE, NPM, CSO, ROA, BVCSO b. Dependent Variable: SALARY
ANOVA
b
Model 1
Sum of Squares
df
Mean Square
F
Sig.
Regression
3552147884156.950
8
444018485519.618
26.874
.000
Residual
3800136284809.520
230
16522331673.085
Total
7352284168966.470
238
a
a. Predictors: (Constant), MVCSO, CFPS, EPS, ROE, NPM, CSO, ROA, BVCSO b. Dependent Variable: SALARY
380 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations SALARY
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
Pearson
SALARY
1.000
.074
.136
.036
-.020
.077
.421
.601
.627
Correlation
ROA
.074
1.000
.537
.150
.001
.630
-.084
-.133
.130
ROE
.136
.537
1.000
.109
.072
.351
-.035
-.046
.090
EPS
.036
.150
.109
1.000
.014
.138
-.163
-.038
-.066
CFPS
-.020
.001
.072
.014
1.000
.008
.046
.035
.037
NPM
.077
.630
.351
.138
.008
1.000
-.185
-.234
.208
CSO
.421
-.084
-.035
-.163
.046
-.185
1.000
.761
.459
BVCSO
.601
-.133
-.046
-.038
.035
-.234
.761
1.000
.643
MVCSO
.627
.130
.090
-.066
.037
.208
.459
.643
1.000
Sig.
SALARY
.
.126
.018
.288
.377
.117
.000
.000
.000
(1-tailed)
ROA
.126
.
.000
.010
.493
.000
.097
.020
.023
ROE
.018
.000
.
.047
.135
.000
.297
.239
.083
EPS
.288
.010
.047
.
.417
.016
.006
.278
.153
CFPS
.377
.493
.135
.417
.
.450
.241
.293
.285
NPM
.117
.000
.000
.016
.450
.
.002
.000
.001
CSO
.000
.097
.297
.006
.241
.002
.
.000
.000
BVCSO
.000
.020
.239
.278
.293
.000
.000
.
.000
MVCSO
.000
.023
.083
.153
.285
.001
.000
.000
.
SALARY
239
239
239
239
239
239
239
239
239
ROA
239
239
239
239
239
239
239
239
239
ROE
239
239
239
239
239
239
239
239
239
EPS
239
239
239
239
239
239
239
239
239
CFPS
239
239
239
239
239
239
239
239
239
NPM
239
239
239
239
239
239
239
239
239
CSO
239
239
239
239
239
239
239
239
239
BVCSO
239
239
239
239
239
239
239
239
239
MVCSO
239
239
239
239
239
239
239
239
239
N
381 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
25.601
.000
B
Std. Error
Beta
(Constant)
296645.568
11587.071
ROA
-23893.248
55880.620
-.029
-.428
.669
ROE
33523.579
16849.962
.112
1.990
.048
EPS
2027.039
1859.181
.054
1.090
.277
CFPS
-81.315
69.140
-.056
-1.176
.241
NPM
.000
.000
.064
.935
.351
CSO
.000
.000
-.038
-.508
.612
BVCSO
.000
.000
.417
4.415
.000
MVCSO
.000
.000
.363
5.068
.000
a. Dependent Variable: SALARY
382 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
95.0% Confidence Interval for
Collinearity
B
Statistics
Correlations
Lower
Upper
Bound
Bound
(Constant)
273815.195
319475.942
ROA
-
86210.112
Zero-order
Partial
Part
Tolerance
VIF
.074
-.028
-
.485
2.061
133996.609
.020
ROE
323.563
66723.595
.136
.130
.094
.705
1.418
EPS
-1636.164
5690.242
.036
.072
.052
.908
1.101
CFPS
-217.544
54.914
-.020
-.077
-
.990
1.010
.056 NPM
.000
.000
.077
.062
.044
.479
2.087
CSO
.000
.000
.421
-.033
-
.397
2.521
.024 BVCSO
.000
.000
.601
.280
.209
.252
3.972
MVCSO
.000
.000
.627
.317
.240
.439
2.279
a. Dependent Variable: SALARY
383 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model Correlations
Covariances
MVCSO
CFPS
EPS
ROE
NPM
CSO
ROA
BVCSO
MVCSO
1.000
-.017
.152
.003
-.413
.094
.004
-.610
CFPS
-.017
1.000
-.020
-.083
-.007
-.035
.044
.012
EPS
.152
-.020
1.000
-.029
-.105
.222
-.069
-.213
ROE
.003
-.083
-.029
1.000
-.022
.011
-.432
-.025
NPM
-.413
-.007
-.105
-.022
1.000
-.016
-.497
.330
CSO
.094
-.035
.222
.011
-.016
1.000
-.060
-.655
ROA
.004
.044
-.069
-.432
-.497
-.060
1.000
.032
BVCSO
-.610
.012
-.213
-.025
.330
-.655
.032
1.000
MVCSO
.000
.000
.002
.000
.000
.000
.001
.000
CFPS
.000
4780.365
-2570.574
-96607.290
.000
.000
169354.428
.000
EPS
.002
-2570.574
3456553.979
-893252.699
-.014
.045
-7204519.764
-.010
ROE
.000
-96607.290
-893252.699
283921226.891
-.026
.021
-406963609.243
-.010
NPM
.000
.000
-.014
-.026
.000
.000
-1.938
.000
CSO
.000
.000
.045
.021
.000
.000
-.363
.000
ROA
.001
169354.428
-7204519.764
-406963609.243
-1.938
-.363
3122643654.363
.044
BVCSO
.000
.000
-.010
-.010
.000
.000
.044
.000
a. Dependent Variable: SALARY
Collinearity Diagnostics Mod
Dimensi
el
on
1
a
Conditi
Variance Proportions
Eigenval
on
(Consta
RO
RO
EP
CFP
NP
CS
BVCS
MVC
ue
Index
nt)
A
E
S
S
M
O
O
SO
1
2.960
1.000
.03
.00
.00
.00
.00
.00
.02
.02
.02
2
2.079
1.193
.00
.08
.08
.01
.00
.07
.00
.00
.01
3
1.018
1.705
.01
.00
.02
.01
.90
.01
.00
.00
.00
4
.964
1.753
.01
.01
.01
.88
.01
.00
.00
.00
.00
5
.705
2.049
.06
.00
.46
.01
.07
.21
.00
.02
.00
6
.563
2.293
.51
.00
.11
.01
.01
.01
.01
.03
.13
7
.362
2.858
.01
.66
.30
.00
.00
.08
.07
.01
.14
8
.241
3.505
.18
.25
.02
.00
.00
.51
.25
.02
.32
9
.108
5.245
.18
.00
.00
.08
.00
.11
.64
.90
.37
a. Dependent Variable: SALARY
384 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Minimum
Maximum
Std. Deviation
N
56313.468750
1063551.000000
122167.8808440
239
-2.540
5.704
1.000
239
8632.783
128498.664
17571.116
239
-611683.937500
8047048.000000
518021.6478762
239
Residual
-349438.8437500
346331.5312500
126360.4336012
239
Std.
-2.719
2.694
.983
239
-2.782
2.899
1.028
239
Deleted
-
1174330.8750000
518137.9064398
239
Residual
7627678.0000000
Stud.
-2.824
2.948
1.032
239
.078
236.854
28.360
239
.000
391.018
25.296
239
.000
.995
.119
239
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value
Residual Stud. Residual
Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: SALARY
385 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
386 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
387 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
388 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
389 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
390 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
391 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 2.2 TSX SMALL (BONUS VS. ROA, ROE, EPS, CFPS, NPM, CSO, BVCSO, MVCSO) Descriptive Statistics Mean
Std. Deviation
N
BONUS
201990.760181
266347.9434976
221
ROA
-.020791
.2190747
221
ROE
-.072322
.6065040
221
EPS
-.098154
4.8507713
221
CFPS
-7.779581
125.9448160
221
NPM
1824082.782805
175351202.6436190
221
CSO
101460866.217195
115539950.1197860
221
BVCSO
351950269.153846
621030526.5724860
221
MVCSO
985116922.045973
1841527802.6529300
221
Model Summary
b
Mode
Change Statistics
l
R
1
R
Adjuste
Squar
dR
R
e
.816
.666
Square
F
Std. Error of the
Chang
Chang
df
Square
Estimate
e
e
1
.654
156726.312550
.666
52.923
8
a
0
Sig. F
Durbin-
Chang
Watso
df2
e
n
21
.000
1.399
2
a. Predictors: (Constant), MVCSO, CFPS, EPS, ROE, NPM, CSO, ROA, BVCSO b. Dependent Variable: BONUS
392 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model 1
Sum of Squares
df
Mean Square
F
Sig.
Regression
10399684887541.900
8
1299960610942.740
52.923
.000
Residual
5207385053650.370
212
24563137045.521
Total
15607069941192.300
220
a
a. Predictors: (Constant), MVCSO, CFPS, EPS, ROE, NPM, CSO, ROA, BVCSO b. Dependent Variable: BONUS
393 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations BONUS
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
Pearson
BONUS
1.000
.148
.134
-.008
.053
.111
.491
.718
.663
Correlation
ROA
.148
1.000
.535
.143
.000
.621
-.085
-.165
.127
ROE
.134
.535
1.000
.096
.070
.340
-.030
-.051
.091
EPS
-.008
.143
.096
1.000
.012
.122
-.168
-.037
-.082
CFPS
.053
.000
.070
.012
1.000
.006
.049
.038
.038
NPM
.111
.621
.340
.122
.006
1.000
-.211
-.296
.192
CSO
.491
-.085
-.030
-.168
.049
-.211
1.000
.730
.395
BVCSO
.718
-.165
-.051
-.037
.038
-.296
.730
1.000
.581
MVCSO
.663
.127
.091
-.082
.038
.192
.395
.581
1.000
Sig.
BONUS
.
.014
.023
.450
.216
.050
.000
.000
.000
(1-tailed)
ROA
.014
.
.000
.017
.499
.000
.104
.007
.029
ROE
.023
.000
.
.079
.150
.000
.331
.224
.090
EPS
.450
.017
.079
.
.431
.035
.006
.293
.113
CFPS
.216
.499
.150
.431
.
.465
.236
.289
.289
NPM
.050
.000
.000
.035
.465
.
.001
.000
.002
CSO
.000
.104
.331
.006
.236
.001
.
.000
.000
BVCSO
.000
.007
.224
.293
.289
.000
.000
.
.000
MVCSO
.000
.029
.090
.113
.289
.002
.000
.000
.
BONUS
221
221
221
221
221
221
221
221
221
ROA
221
221
221
221
221
221
221
221
221
ROE
221
221
221
221
221
221
221
221
221
EPS
221
221
221
221
221
221
221
221
221
CFPS
221
221
221
221
221
221
221
221
221
NPM
221
221
221
221
221
221
221
221
221
CSO
221
221
221
221
221
221
221
221
221
BVCSO
221
221
221
221
221
221
221
221
221
MVCSO
221
221
221
221
221
221
221
221
221
N
394 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model Summary
b
Model
Change Statistics Adjusted R
1
.816
a
R
R
R
Std. Error of the
Square
F
Square
Square
Estimate
Change
Change
df1
.666
.654
156726.3125500
.666
52.923
8
Sig. F
Durbin-
df2
Change
Watson
212
.000
1.399
a. Predictors: (Constant), MVCSO, CFPS, EPS, ROE, NPM, CSO, ROA, BVCSO b. Dependent Variable: BONUS
ANOVA
b
Model 1
Sum of Squares
df
Mean Square
F
Sig.
Regression
10399684887541.900
8
1299960610942.740
52.923
.000
Residual
5207385053650.370
212
24563137045.521
Total
15607069941192.300
220
a
a. Predictors: (Constant), MVCSO, CFPS, EPS, ROE, NPM, CSO, ROA, BVCSO b. Dependent Variable: BONUS
395 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
5.568
.000
B
Std. Error
Beta
(Constant)
82212.645
14765.798
ROA
115122.106
68958.945
.095
1.669
.097
ROE
13563.113
20725.179
.031
.654
.514
EPS
-923.211
2287.055
-.017
-.404
.687
CFPS
38.542
84.321
.018
.457
.648
NPM
.000
.000
.198
3.461
.001
CSO
.000
.000
-.072
-1.196
.233
BVCSO
.000
.000
.716
9.666
.000
MVCSO
.000
.000
.221
3.942
.000
a. Dependent Variable: BONUS
396 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
95.0% Confidence Interval for B
Collinearity Statistics
Correlations
Lower
Upper
Bound
Bound
(Constant)
53106.052
111319.238
ROA
-
Zero-order
Partial
Part
Tolerance
VIF
251055.151
.148
.114
.066
.489
2.044
54416.939
.134
.045
.026
.707
1.415
3585.070
-.008
-.028
-
.907
1.102
20810.940 ROE
27290.713
EPS
-5431.493
.016 CFPS
-127.674
204.758
.053
.031
.018
.990
1.010
NPM
.000
.000
.111
.231
.137
.483
2.072
CSO
.000
.000
.491
-.082
-
.440
2.275
.047 BVCSO
.000
.000
.718
.553
.383
.287
3.489
MVCSO
.000
.000
.663
.261
.156
.502
1.990
a. Dependent Variable: BONUS
397 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model Correlations
Covariances
MVCSO
CFPS
EPS
ROE
NPM
CSO
ROA
BVCSO
MVCSO
1.000
-.018
.164
.010
-.399
.096
-.015
-.584
CFPS
-.018
1.000
-.020
-.081
-.008
-.037
.044
.011
EPS
.164
-.020
1.000
-.016
-.097
.227
-.084
-.217
ROE
.010
-.081
-.016
1.000
-.023
.018
-.438
-.041
NPM
-.399
-.008
-.097
-.023
1.000
-.017
-.481
.350
CSO
.096
-.037
.227
.018
-.017
1.000
-.081
-.640
ROA
-.015
.044
-.084
-.438
-.481
-.081
1.000
.054
BVCSO
-.584
.011
-.217
-.041
.350
-.640
.054
1.000
MVCSO
.000
.000
.003
.002
.000
.000
-.008
.000
CFPS
.000
7110.106
-3891.575
-142312.907
.000
.000
258513.367
.000
EPS
.003
-3891.575
5230619.620
-747871.989
-.019
.071
-13267223.175
-.016
ROE
.002
-
-747871.989
429533053.408
-.042
.051
-625357395.950
-.027
142312.907 NPM
.000
.000
-.019
-.042
.000
.000
-2.878
.000
CSO
.000
.000
.071
.051
.000
.000
-.769
.000
ROA
-.008
258513.367
-
-
-
-.769
4755336086.179
.118
13267223.175
625357395.950
2.878
-.016
-.027
.000
.000
.118
.000
BVCSO
.000
.000
a. Dependent Variable: BONUS
398 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics
a
Dimension Condition
Variance Proportions
Eigenvalue
Index
(Constant)
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
1
2.954
1.000
.03
.01
.01
.00
.00
.00
.02
.02
.02
2
2.020
1.209
.01
.08
.08
.01
.00
.07
.00
.00
.02
3
1.020
1.702
.01
.00
.02
.00
.90
.01
.00
.00
.00
4
.970
1.745
.01
.00
.01
.88
.00
.00
.00
.00
.00
5
.728
2.015
.06
.00
.44
.00
.08
.20
.00
.02
.01
6
.558
2.300
.45
.00
.08
.01
.01
.01
.02
.03
.21
7
.374
2.812
.06
.59
.35
.00
.00
.04
.08
.02
.14
8
.256
3.398
.20
.32
.03
.00
.00
.56
.21
.03
.26
9
.121
4.942
.18
.00
.00
.09
.00
.11
.66
.88
.34
a. Dependent Variable: BONUS
399 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
-70650.000000
1639815.125000
201990.760181
217419.6286985
221
-1.254
6.613
.000
1.000
221
10859.135
156678.016
22355.996
22423.052
221
Adjusted
-
1571490.750000
167161.157848
461453.2599830
221
Predicted
5704014.000000 466955.5625000
.0000000
153850.3560673
221
-2.269
2.979
.000
.982
221
-2.442
2.993
.019
1.021
221
Deleted
-
5704014.0000000
34829.6023329
426598.4980272
221
Residual
411733.5937500
Stud.
-2.471
3.051
.020
1.027
221
.061
218.869
7.964
27.958
221
.000
147.085
.710
9.901
221
.000
.995
.036
.127
221
Predicted Value Std. Predicted Value Standard Error of Predicted Value
Value Residual
355620.2812500
Std. Residual Stud. Residual
Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: BONUS
400 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
401 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
402 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
403 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
404 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
405 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
406 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 2.3 NYSE SMALL (SALARY VS. ROA, ROE, EPS, CFPS, NPM, CSO, BVCSO, MVCSO) Descriptive Statistics Mean
Std. Deviation
N
SALARY
455481.100418
159718.4622716
239
ROA
.011832
.1680427
239
ROE
.006062
.4639709
239
EPS
.234937
2.7676069
239
CFPS
9.417866
52.8110042
239
NPM
14392855.799163
100607363.7383680
239
CSO
61250931.104603
150391013.4458700
239
BVCSO
59282288.841004
198361462.4902860
239
MVCSO
489201027.899582
550184726.3563180
239
Model Summary
b
Mod
Change Statistics
el
R Durbin
Squ Adjuste R 1
.444
a
are
Sig. F
-
Chang
Watso
R
dR
Std. Error of
Cha
F
df
Square
Square
the Estimate
nge
Change
1
df2
e
n
.197
.169
289635.651
.19
7.045
8
23
.000
.706
7
0
407 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
1194890801815.360
8
149361350226.920
7.045
.000
Residual
4876486149498.230
230
21202113693.471
Total
6071376951313.590
238
a
a. Predictors: (Constant), MVCSO, CFPS, CSO, ROA, BVCSO, ROE, EPS, NPM b. Dependent Variable: SALARY
408 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations SALARY
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
SALARY
1.000
-.068
-.148
-.052
.050
-.173
.085
.243
.148
ROA
-.068
1.000
.712
.679
-.088
.488
.047
.083
.226
ROE
-.148
.712
1.000
.617
-.036
.629
-.035
.068
.314
EPS
-.052
.679
.617
1.000
-.025
.680
.071
.177
.420
CFPS
.050
-.088
-.036
-.025
1.000
-.018
-.034
-.046
-.102
NPM
-.173
.488
.629
.680
-.018
1.000
-.224
.061
.590
CSO
.085
.047
-.035
.071
-.034
-.224
1.000
.412
.113
BVCSO
.243
.083
.068
.177
-.046
.061
.412
1.000
.238
MVCSO
.148
.226
.314
.420
-.102
.590
.113
.238
1.000
Sig.
SALARY
.
.146
.011
.213
.222
.004
.096
.000
.011
(1-tailed)
ROA
.146
.
.000
.000
.086
.000
.236
.100
.000
ROE
.011
.000
.
.000
.289
.000
.293
.147
.000
EPS
.213
.000
.000
.
.351
.000
.136
.003
.000
CFPS
.222
.086
.289
.351
.
.393
.300
.241
.057
NPM
.004
.000
.000
.000
.393
.
.000
.172
.000
CSO
.096
.236
.293
.136
.300
.000
.
.000
.041
BVCSO
.000
.100
.147
.003
.241
.172
.000
.
.000
MVCSO
.011
.000
.000
.000
.057
.000
.041
.000
.
SALARY
239
239
239
239
239
239
239
239
239
ROA
239
239
239
239
239
239
239
239
239
ROE
239
239
239
239
239
239
239
239
239
EPS
239
239
239
239
239
239
239
239
239
CFPS
239
239
239
239
239
239
239
239
239
NPM
239
239
239
239
239
239
239
239
239
CSO
239
239
239
239
239
239
239
239
239
BVCSO
239
239
239
239
239
239
239
239
239
MVCSO
239
239
239
239
239
239
239
239
239
Pearson Correlation
N
409 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
29.361
.000
B
Std. Error
Beta
(Constant)
407648.314
13883.974
ROA
82157.386
90923.285
.086
.904
.367
ROE
-32778.604
32697.141
-.095
-1.002
.317
EPS
6074.542
5754.190
.105
1.056
.292
CFPS
278.598
181.192
.092
1.538
.126
NPM
-.001
.000
-.512
-4.628
.000
CSO
.000
.000
-.186
-2.568
.011
BVCSO
.000
.000
.243
3.641
.000
MVCSO
.000
.000
.389
4.897
.000
a. Dependent Variable: SALARY
410 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
95.0% Confidence Interval for B
Collinearity Statistics
Correlations
Lower
Upper
Bound
Bound
(Constant)
380292.279
435004.349
ROA
-96991.653
ROE
-97202.819
Zero-order
Partial
Part
Tolerance
VIF
261306.424
-.068
.059
.053
.382
2.621
31645.611
-.148
-.066
-
.387
2.583
.059 EPS
-5263.122
17412.206
-.052
.069
.062
.351
2.847
CFPS
-78.411
635.607
.050
.101
.091
.973
1.028
NPM
-.001
.000
-.173
-.292
-
.286
3.499
.666
1.501
.273 CSO
.000
.000
.085
-.167
.152
BVCSO
.000
.000
.243
.233
.215
.785
1.273
MVCSO
.000
.000
.148
.307
.289
.554
1.804
a. Dependent Variable: SALARY
411 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
MVCSO
CFPS
EPS
ROE
NPM
CSO
ROA
BVCSO
MVCSO
1.000
.118
-.253
.093
-.128
.058
-.006
-.522
CFPS
.118
1.000
-.014
.109
.021
-.021
-.049
-.048
EPS
-.253
-.014
1.000
-.035
-.359
-.053
-.195
.431
ROE
.093
.109
-.035
1.000
.033
-.515
-.442
.082
NPM
-.128
.021
-.359
.033
1.000
.008
-.079
-.005
CSO
.058
-.021
-.053
-.515
.008
1.000
-.005
-.353
ROA
-.006
-.049
-.195
-.442
-.079
-.005
1.000
-.447
BVCSO
-.522
-.048
.431
.082
-.005
-.353
-.447
1.000
MVCSO
.000
.000
.000
.195
.000
.044
-.001
.000
CFPS
.000
32830.674
.000
1793264.821
.000
-123495.561
-
-.002
Model Correlations
Covariances
50713.0 87 EPS
.000
.000
.000
-.245
.000
-.133
-.086
.000
ROE
.195
1793264.821
-.245
8267043834.904
.161
-
-
1.316
1531409629.963
231299 495.473
NPM
.000
.000
.000
.161
.000
.014
-.024
.000
CSO
.044
-123495.561
-.133
-
.014
1069103002.808
-
-2.024
1531409629.963
920833. 140
ROA
-.001
-50713.087
-.086
-231299495.473
-.024
-920833.140
331107
-.452
06.463 BVCSO
.000
-.002
.000
1.316
.000
-2.024
-.452
a. Dependent Variable: SALARY
412 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
.000
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics
a
Dimension Condition
Variance Proportions
Eigenvalue
Index
(Constant)
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
1
3.286
1.000
.01
.02
.02
.02
.00
.02
.00
.01
.01
2
2.014
1.277
.06
.01
.02
.01
.01
.01
.07
.06
.02
3
1.080
1.744
.03
.01
.00
.00
.46
.01
.07
.09
.01
4
.882
1.930
.04
.02
.01
.01
.46
.02
.07
.05
.06
5
.626
2.291
.10
.09
.01
.00
.01
.05
.11
.51
.00
6
.415
2.815
.15
.08
.12
.18
.00
.03
.30
.26
.02
7
.338
3.117
.09
.14
.46
.25
.00
.03
.17
.02
.02
8
.205
4.001
.41
.55
.19
.29
.05
.00
.00
.00
.35
9
.152
4.646
.12
.08
.17
.24
.01
.83
.21
.00
.50
413 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
a
Minimum 154434.640625
Maximum 848607.687500
Mean 455481.100418
Std. Deviation 70855.8366506
N 239
-4.249
5.548
.000
1.000
239
10210.166
116892.563
21698.510
18137.172
239
93131.992188
737968.187500
455132.683144
70569.7874119
239
417628.0000000 -2.868
405295.3437500
.0000000
143141.3203898
239
.000
.983
239
.001
1.025
239
348.4172744
159483.1314108
239
.001
1.032
239
7.967
19.482
239
.017
.120
239
.033
.082
239
Std. 2.783 Residual Stud. -3.019 3.025 Residual Deleted 707067.7500000 Residual 533895.1250000 Stud. -3.074 3.080 Deleted Residual Mahal. .174 152.385 Distance Cook's .000 1.688 Distance Centered .001 .640 Leverage Value a. Dependent Variable: SALARY
414 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
415 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
416 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
417 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
418 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
419 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
420 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 2.4 NYSE SMALL SIZE COMPANIES (BONUS VS. ROA, ROE, EPS, NPM, CSO, BVCSO, AND MVCSO) Descriptive Statistics Mean
Std. Deviation
N
BONUS
189348.829060
254411.5504505
234
ROA
.011748
.1683091
234
ROE
.016248
.4406280
234
EPS
.184829
2.7600652
234
CFPS
9.641880
53.3554753
234
NPM
14656209.128205
101665400.9841100
234
CSO
56399223.649573
145417830.8521170
234
BVCSO
55612765.098291
195725655.1108930
234
MVCSO
466926048.435897
515810452.8039510
234
421 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations BONUS
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
BONUS
1.000
.039
-.051
.050
-.066
-.076
.045
.407
-.020
ROA
.039
1.000
.735
.669
-.089
.482
.031
.071
.211
ROE
-.051
.735
1.000
.633
-.042
.654
-.055
.050
.326
EPS
.050
.669
.633
1.000
-.023
.690
.034
.131
.401
CFPS
-.066
-.089
-.042
-.023
1.000
-.019
-.030
-.042
-.102
NPM
-.076
.482
.654
.690
-.019
1.000
-.230
.053
.640
CSO
.045
.031
-.055
.034
-.030
-.230
1.000
.384
.036
BVCSO
.407
.071
.050
.131
-.042
.053
.384
1.000
.195
MVCSO
-.020
.211
.326
.401
-.102
.640
.036
.195
1.000
Sig.
BONUS
.
.276
.220
.224
.157
.122
.248
.000
.382
(1-tailed)
ROA
.276
.
.000
.000
.088
.000
.320
.139
.001
ROE
.220
.000
.
.000
.262
.000
.201
.225
.000
EPS
.224
.000
.000
.
.363
.000
.301
.022
.000
CFPS
.157
.088
.262
.363
.
.387
.325
.260
.059
NPM
.122
.000
.000
.000
.387
.
.000
.209
.000
CSO
.248
.320
.201
.301
.325
.000
.
.000
.291
BVCSO
.000
.139
.225
.022
.260
.209
.000
.
.001
MVCSO
.382
.001
.000
.000
.059
.000
.291
.001
.
BONUS
234
234
234
234
234
234
234
234
234
ROA
234
234
234
234
234
234
234
234
234
ROE
234
234
234
234
234
234
234
234
234
EPS
234
234
234
234
234
234
234
234
234
CFPS
234
234
234
234
234
234
234
234
234
NPM
234
234
234
234
234
234
234
234
234
CSO
234
234
234
234
234
234
234
234
234
BVCSO
234
234
234
234
234
234
234
234
234
MVCSO
234
234
234
234
234
234
234
234
234
Pearson Correlation
N
422 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model Summary Mode
R
l
b
R
Adjuste
Std. Error of the
Squar
dR
Estimate
e
Square
Change Statistics
Durbin-
R
F
df
Square
Chang
1
Chang
e
df2
Sig. F Chang
Watso n
e
e 1
.472
.223
.195
a
ANOVA
.223
8.058
8
6
22
.000
1.187
5
b
Model 1
228253.199897
Sum of Squares
df
Mean Square
F
Sig.
Regression
3358587487325.130
8
419823435915.642
8.058
.000
Residual
11722392734284.000
225
52099523263.485
Total
15080980221609.100
233
a
a. Predictors: (Constant), MVCSO, CFPS, EPS, ROE, NPM, CSO, ROA, BVCSO b. Dependent Variable: BONUS
423 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
8.201
.000
B
Std. Error
Beta
(Constant)
186022.536
22683.520
ROA
124905.018
146657.059
.083
.852
.395
ROE
-56169.504
58266.226
-.097
-.964
.336
EPS
15153.037
9094.391
.164
1.666
.097
CFPS
-242.893
284.306
-.051
-.854
.394
NPM
-.001
.000
-.230
-
.054
1.941 CSO
.000
.000
-.206
-
.004
2.939 BVCSO
.001
.000
.477
7.331
.000
MVCSO
.000
.000
-.015
-.178
.859
a. Dependent Variable: BONUS
424 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
95.0% Confidence
Correlations
Collinearity
Interval for B
Statistics
Lower
Upper
Zero-order
Partial
Part
Tolerance
VIF
Bound
Bound
(Constant)
141323.222
230721.850
ROA
-
413902.048
.039
.057
.050
.367
2.725
58647.788
-.051
-.064
-
.339
2.948
164092.013 ROE
170986.796
.057
EPS
-2768.036
33074.111
.050
.110
.098
.355
2.818
CFPS
-803.135
317.350
-.066
-.057
-
.972
1.029
.245
4.082
.703
1.423
.050 NPM
-.001
.000
-.076
-.128
.114
CSO
-.001
.000
.045
-.192
.173
BVCSO
.000
.001
.407
.439
.431
.816
1.225
MVCSO
.000
.000
-.020
-.012
-
.510
1.960
.010 a. Dependent Variable: BONUS
425 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations Model
a
MVC
CSO
CFPS
ROA
-.223
.125
.068
SO Correlation
MVCSO
s
Covariance s
1.00
BVCS
EPS
ROE
NPM
-.120
.062
.096
-.585
O
0 CSO
-.223
1.000
-.012
-.018
-.352
-.201
-.065
.403
CFPS
.125
-.012
1.000
.103
.017
-.040
-.012
-.059
ROA
.068
-.018
.103
1.000
.003
-.422
-.559
.127
BVCSO
-.120
-.352
.017
.003
1.000
-.044
.020
-.011
EPS
.062
-.201
-.040
-.422
-.044
1.000
.018
-.471
ROE
.096
-.065
-.012
-.559
.020
.018
1.000
-.398
NPM
-.585
.403
-.059
.127
-.011
-.471
-.398
1.000
MVCSO
.000
.000
.001
.407
.000
.023
.227
.000
CSO
.000
.000
.000
-.329
.000
-.224
-.463
.000
CFPS
.001
.000
80829.672
4279007.690
.000
-102489.975
-196254.242
-.005
ROA
.407
-.329
4279007.69
21508292843.8
.043
-
-
5.535
0
83
563349977.0
4776007438.2
57
24
BVCSO
.000
.000
.000
.043
.000
-.034
.099
.000
EPS
.023
-.224
-
-563349977.057
-.034
82707942.53
9340694.279
-
ROE
.227
-.463
-
-
.099
196254.242
4776007438.22
102489.975
1 9340694.279
1.273 3394953101.3
-
19
6.883
-6.883
.000
4 NPM
.000
.000
-.005
5.535
.000
-1.273
a. Dependent Variable: BONUS
426 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics
a
Dimensio
Eigenvalu
Conditio
n
e
n Index
Variance Proportions (Constan
RO
RO
EP
CFP
NP
CS
BVCS
MVCS
t)
A
E
S
S
M
O
O
O
1
3.284
1.000
.01
.02
.02
.02
.00
.02
.00
.01
.01
2
1.987
1.286
.06
.01
.01
.01
.01
.00
.07
.06
.02
3
1.093
1.733
.03
.01
.00
.00
.37
.01
.10
.11
.01
4
.903
1.907
.02
.02
.01
.01
.54
.01
.06
.03
.05
5
.647
2.253
.09
.07
.01
.00
.02
.04
.12
.55
.00
6
.434
2.751
.13
.11
.06
.16
.00
.04
.34
.22
.01
7
.325
3.181
.10
.07
.39
.37
.00
.03
.15
.01
.02
8
.200
4.056
.38
.59
.28
.20
.04
.00
.00
.00
.30
9
.128
5.070
.19
.09
.22
.23
.01
.85
.15
.00
.58
a. Dependent Variable: BONUS
427 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
a
Minimum
Maximum
Mean
Std. Deviation
N
-90729.726563
1522727.125000
189348.829060
120060.5621018
234
-2.333
11.106
.000
1.000
234
16084.830
185210.578
34332.322
28786.469
234
-178757.937500
745013.437500
184558.765689
91334.3253984
234
452981.4062500 -1.985
632403.9375000
.0000000
224300.4646237
234
.000
.983
234
.008
1.017
234
4790.0633705
247914.8264984
234
.011
1.023
234
7.966
19.832
234
.016
.180
234
.034
.085
234
Std. 2.771 Residual Stud. -2.033 3.578 Residual Deleted 1397218.5000000 Residual 475392.6875000 Stud. -2.047 3.676 Deleted Residual Mahal. .161 152.414 Distance Cook's .000 2.741 Distance Centered .001 .654 Leverage Value a. Dependent Variable: BONUS
428 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
429 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
430 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
431 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
432 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
433 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 2.5 TSX MEDIUM SIZE COMPANIES (SALARY VS. ROA, ROE, EPS, NPM, CSO, BVCSO, AND MVCSO) Descriptive Statistics Mean
Std. Deviation
N
SALARY
618000.05
240524.107
233
ROA
.061545
.0854765
233
ROE
-39.786236
608.7453585
233
EPS
1.1839
1.84070
233
CFPS
2.2741
2.09288
233
NPM
95704214.66
188119790.182
233
CS
134506574.45
152754366.326
233
959204323.00
1640724033.172
233
2321139216.98
2922821570.278
233
OUTSTANDING BOOK VALUE OF CS OUTSTANDING MARKET VALUE OF CS OUTSTANDING Model Summary Model
R
b
R
Adjusted
Std. Error of
Change Statistics
Square
R
the Estimate
R
F
Square
Change
Square
Durbindf1
df2
Sig. F
Watson
Change
Change 1
.373
a
.139
.108
227119.028
.139
4.524
8
224
.000
.678
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VAUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: SALARY
Correlations
434 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SALARY
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
SALARY
1.000
.010
.039
.005
.028
.182
.294
.330
.310
ROA
.010
1.000
-.028
.694
.257
.665
-.153
-.140
.031
ROE
.039
-.028
1.000
.153
-.008
.068
.044
.034
.052
EPS
.005
.694
.153
1.000
.566
.579
-.238
-.194
-.007
CFPS
.028
.257
-.008
.566
1.000
.280
-.334
-.229
-.025
NPM
.182
.665
.068
.579
.280
1.000
.139
.173
.250
CSO
.294
-.153
.044
-.238
-.334
.139
1.000
.883
.694
BVCSO
.330
-.140
.034
-.194
-.229
.173
.883
1.000
.724
MVCSO
.310
.031
.052
-.007
-.025
.250
.694
.724
1.000
Sig.
SALARY
.
.442
.276
.470
.335
.003
.000
.000
.000
(1-tailed)
ROA
.442
.
.336
.000
.000
.000
.010
.016
.319
ROE
.276
.336
.
.010
.452
.152
.250
.304
.217
EPS
.470
.000
.010
.
.000
.000
.000
.001
.460
CFPS
.335
.000
.452
.000
.
.000
.000
.000
.354
NPM
.003
.000
.152
.000
.000
.
.017
.004
.000
CSO
.000
.010
.250
.000
.000
.017
.
.000
.000
BVCSO
.000
.016
.304
.001
.000
.004
.000
.
.000
MVCSO
.000
.319
.217
.460
.354
.000
.000
.000
.
SALARY
233
233
233
233
233
233
233
233
233
ROA
233
233
233
233
233
233
233
233
233
ROE
233
233
233
233
233
233
233
233
233
EPS
233
233
233
233
233
233
233
233
233
CFPS
233
233
233
233
233
233
233
233
233
NPM
233
233
233
233
233
233
233
233
233
CSO
233
233
233
233
233
233
233
233
233
BVCSO
233
233
233
233
233
233
233
233
233
MVCSO
233
233
233
233
233
233
233
233
233
Pearson Correlation
N
435 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
1
Sum of Squares
df
Mean Square
F
Sig.
Regression
1867024436411.670
8
233378054551.458
4.524
.000
Residual
11554603812437.700
224
51583052734.097
Total
13421628248849.400
232
a
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VALUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: SALARY Coefficients Model
a
Unstandardized Coefficients
Standardized
t
Sig.
16.066
.000
Coefficients B
Std. Error
Beta
(Constant)
538953.683
33545.963
ROA
-117610.066
295554.602
-.042
-.398
.691
ROE
9.616
25.697
.024
.374
.709
EPS
-8196.198
14363.007
-.063
-.571
.569
CFPS
10223.603
9679.319
.089
1.056
.292
NPM
.000
.000
.153
1.628
.105
CSO
.000
.000
.021
.146
.884
BVCSO
.000
.000
.209
1.473
.142
MVCSO
.000
.000
.108
1.122
.263
436 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
95.0% Confidence Interval
Correlations
Collinearity
for B Lower Bound
Statistics Upper
Zero-order
Partial
Part
Tolerance
VIF
.010
-.027
-
.348
2.870
Bound (Constant)
472847.639
605059.726
ROA
-700033.205
464813.074
.025 ROE
-41.022
60.254
.039
.025
.023
.909
1.101
EPS
-36500.097
20107.701
.005
-.038
-
.318
3.144
.035 CFPS
-8850.568
29297.775
.028
.070
.065
.542
1.846
NPM
.000
.000
.182
.108
.101
.434
2.306
CSO
.000
.000
.294
.010
.009
.189
5.296
BVCSO
.000
.000
.330
.098
.091
.191
5.226
MVCSO
.000
.000
.310
.075
.070
.416
2.404
a. Dependent Variable: SALARY
437 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations Model
a
MVCS
CSO
CFPS
ROA
O Correlation
MVCS
s
O
BVC
EPS
ROE
NPM
SO
1.000
.021
-.042
-.210
-.001
-.309
-.110
-.246
CSO
.021
1.000
-.276
-.505
-.167
.039
-.520
.002
CFPS
-.042
-.276
1.000
.159
-.060
.026
.224
-.012
ROA
-.210
-.505
.159
1.000
-.133
-.048
.299
.287
BVCS
-.001
-.167
-.060
-.133
1.000
-.130
-.492
-.087
-.309
.039
.026
-.048
-.130
1.00
.111
-.711
O EPS
0 ROE
-.110
-.520
.224
.299
-.492
.111
1.000
.071
NPM
-.246
.002
-.012
.287
-.087
-.711
.071
1.00 0
Covariance
MVCS
s
O CSO
.000
.002
.000
-.016
.000
.000
-.257
.000
.002
206295968.9
-
-
-.288
.012
-
.006
77
101728.96
70223674.
2207770217.3
2
539
93
CFPS
.000
-101728.962
660.322
39546.622
.000
.000
1702540.754
.000
ROA
-.016
-
39546.622
93689208.
-.155
-.010
854729030.53
.625
70223674.53
937
1
9 BVCS
.000
-.288
.000
-.155
.000
.000
-17.488
.000
EPS
.000
.012
.000
-.010
.000
.000
.680
.000
ROE
-.257
-
1702540.7
854729030
-
.680
87352523019.
4.69
2207770217.
54
.531
17.48
231
7
4.697
.000
O
393 NPM
.000
.006
8 .000
.625
.000
.000
a. Dependent Variable: SALARY
438 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics Dimension
a
Eigenvalue
Condition Index
Variance Proportions (Constant)
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
1
4.620
1.000
.01
.01
.00
.01
.01
.01
.00
.00
.01
2
1.813
1.596
.00
.02
.00
.02
.01
.01
.01
.02
.02
3
1.030
2.118
.00
.00
.83
.00
.00
.00
.00
.00
.00
4
.666
2.633
.06
.03
.04
.00
.11
.17
.00
.00
.00
5
.295
3.958
.18
.21
.02
.02
.19
.07
.02
.01
.07
6
.227
4.509
.07
.09
.01
.16
.04
.51
.01
.00
.31
7
.182
5.044
.02
.03
.03
.40
.00
.08
.04
.13
.48
8
.105
6.647
.18
.58
.06
.36
.40
.13
.03
.26
.10
9
.062
8.654
.48
.05
.00
.03
.23
.01
.89
.57
.01
a. Dependent Variable: SALARY
439 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
475058.59
1266154.38
618000.05
89707.966
233
-1.593
7.225
.000
1.000
233
16451.801
227119.016
37036.676
24968.756
233
481995.28
882285440.00
4402611.14
57759984.678
233
Residual
-603579.500
671380.313
.000
223168.830
233
Std.
-2.658
2.956
.000
.983
233
-2.698
2.978
-.004
1.005
233
Deleted
-
681458.188
-
57769790.421
233
Residual
881810432.000
Stud.
-2.737
3.032
-.003
1.011
233
.222
231.004
7.966
19.592
233
.000
1674946.250
7188.616
109729.375
233
.001
.996
.034
.084
233
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value
Residual Stud. Residual 3784611.091
Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: SALARY
440 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
441 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
442 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
443 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
444 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
445 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
446 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 2.6 TSX MEDIUM SIZE COMPANIES (BONUS VS. ROA, ROE, EPS, NPM, CSO, BVCSO, AND MVCSO) Descriptive Statistics Mean
Std. Deviation
N
BONUS
699323.44
623359.240
226
ROA
.061231
.0834123
226
ROE
-41.023163
618.1008259
226
EPS
1.2141
1.86644
226
CFPS
2.2991
2.11438
226
NPM
92464792.10
188517852.120
226
CS
128765818.60
145347464.253
226
900398886.10
1567204161.297
226
2241512051.76
2869166100.639
226
OUTSTANDING BOOK VALUE OF CS OUTSTANDING MARKET VALUE OF CS OUTSTANDING Model Summary Model
R
b
R
Adjusted
Std. Error of
Change Statistics
Square
R
the Estimate
R
F
Square
Change
Square
Durbindf1
df2
Sig. F
Watson
Change
Change 1
.301
a
.091
.057
605225.563
.091
2.711
8
217
.007
1.124
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VAUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: BONUS
447 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations BONUS
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
BONUS
1.000
.012
.075
.054
-.002
.142
.240
.270
.211
ROA
.012
1.000
-.029
.727
.282
.666
-.200
-.213
-.012
ROE
.075
-.029
1.000
.154
-.007
.067
.045
.033
.051
EPS
.054
.727
.154
1.000
.572
.587
-.245
-.197
-.003
CFPS
-.002
.282
-.007
.572
1.000
.298
-.328
-.216
-.005
NPM
.142
.666
.067
.587
.298
1.000
.106
.136
.223
CSO
.240
-.200
.045
-.245
-.328
.106
1.000
.873
.674
BVCSO
.270
-.213
.033
-.197
-.216
.136
.873
1.000
.701
MVCSO
.211
-.012
.051
-.003
-.005
.223
.674
.701
1.000
Sig.
BONUS
.
.429
.131
.211
.487
.017
.000
.000
.001
(1-tailed)
ROA
.429
.
.330
.000
.000
.000
.001
.001
.427
ROE
.131
.330
.
.010
.457
.157
.252
.309
.221
EPS
.211
.000
.010
.
.000
.000
.000
.001
.482
CFPS
.487
.000
.457
.000
.
.000
.000
.001
.471
NPM
.017
.000
.157
.000
.000
.
.056
.021
.000
CSO
.000
.001
.252
.000
.000
.056
.
.000
.000
BVCSO
.000
.001
.309
.001
.001
.021
.000
.
.000
MVCSO
.001
.427
.221
.482
.471
.000
.000
.000
.
BONUS
226
226
226
226
226
226
226
226
226
ROA
226
226
226
226
226
226
226
226
226
ROE
226
226
226
226
226
226
226
226
226
EPS
226
226
226
226
226
226
226
226
226
CFPS
226
226
226
226
226
226
226
226
226
NPM
226
226
226
226
226
226
226
226
226
CSO
226
226
226
226
226
226
226
226
226
BVCSO
226
226
226
226
226
226
226
226
226
MVCSO
226
226
226
226
226
226
226
226
226
Pearson Correlation
N
448 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
7943105001946.560
8
992888125243.320
2.711
.007
Residual
79486662038125.200
217
366297981742.512
Total
87429767040071.800
225
a
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VAUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: BONUS
Coefficients Model
a
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
6.093
.000
B
Std. Error
Beta
(Constant)
558190.411
91618.545
ROA
-
880136.450
-.054
-.456
.649
401407.692 ROE
44.314
68.984
.044
.642
.521
EPS
30335.164
40176.224
.091
.755
.451
CFPS
-643.899
26174.528
-.002
-.025
.980
NPM
.000
.000
.086
.880
.380
CSO
.000
.001
.045
.312
.755
BVCSO
.000
.000
.220
1.530
.127
MVCSO
.000
.000
.004
.044
.965
a. Dependent Variable: BONUS
449 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
95.0% Confidence Interval
Correlations
Collinearity
for B Lower Bound
Statistics Upper
Zero-order
Partial
Part
Tolerance
VIF
.012
-.031
-
.302
3.311
Bound (Constant)
377614.263
738766.560
ROA
-
1333302.790
2136118.174
.030
ROE
-91.651
180.278
.075
.044
.042
.895
1.117
EPS
-48850.419
109520.747
.054
.051
.049
.290
3.454
CFPS
-52232.750
50944.951
-.002
-.002
-
.532
1.881
.002 NPM
.000
.001
.142
.060
.057
.435
2.297
CSO
-.001
.001
.240
.021
.020
.201
4.965
BVCSO
.000
.000
.270
.103
.099
.202
4.941
MVCSO
.000
.000
.211
.003
.003
.443
2.258
a. Dependent Variable: BONUS
450 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations Model
a
MVCS
CSO
CFPS
ROA
EPS
ROE
1.000
.027
-.043
-.214
.000
-.296
-.104
CSO
.027
1.000
-.298
-.516
-.109
-.041
-.577
.044
CFPS
-.043
-.298
1.000
.171
-.076
.054
.251
-
ROA
-.214
-.516
.171
1.000
-.149
-.022
.315
.271
BVCS
.000
-.109
-.076
-.149
1.000
-.156
-.501
-
O Correlation
MVCS
s
O
BVCS
NP
O
M .250
.029
O EPS
.070 -.296
-.041
.054
-.022
-.156
1.000
.207
.705
ROE
-.104
-.577
.251
.315
-.501
.207
1.000
.007
NPM
-.250
.044
-.029
.271
-.070
-.705
.007
1.00 0
Covarianc
MVCS
es
O CSO
.000
.023
.000
-.118
.000
.000
-1.929
.000
.023
1614129013.46
-825924.586
-
-1.425
-.095
-
1.09
20401420058.65
8
9
543049959.67 5
7
CFPS
.000
-825924.586
4758.799
309617.848
-.002
.000
15229476.158
-
ROA
-.118
-
309617.848
685105910.90
-1.265
-.033
7263748861.353
BVCS
.000
-1.425
-.002
-1.265
.000
.000
-142.948
.000
EPS
.000
-.095
.000
-.033
.000
.000
10.424
.000
ROE
-1.929
-
15229476.1
7263748861.3
-
10.42
774640170966.3
3.70
20401420058.6
58
53
142.94
4
81
7
.000
3.707
.000
.001 543049959.675
6
4.39 2
O
57 NPM
.000
1.098
8 -.001
4.392
.000
a. Dependent Variable: BONUS
451 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics
a
Dimensio
Eigenvalu
Conditio
n
e
n Index
Variance Proportions (Constan
RO
RO
EP
CFP
NP
CS
BVCS
MVCS
t)
A
E
S
S
M
O
O
O
1
4.578
1.000
.01
.01
.00
.01
.01
.01
.00
.00
.01
2
1.861
1.568
.00
.01
.00
.02
.01
.01
.01
.02
.02
3
1.030
2.108
.00
.00
.82
.00
.00
.00
.00
.00
.00
4
.649
2.656
.06
.02
.04
.00
.11
.20
.00
.01
.00
5
.303
3.890
.17
.15
.02
.01
.20
.05
.02
.01
.10
6
.234
4.424
.05
.09
.00
.11
.06
.44
.01
.01
.38
7
.190
4.913
.04
.01
.03
.35
.00
.13
.02
.17
.42
8
.090
7.129
.17
.68
.09
.47
.37
.14
.05
.27
.05
9
.066
8.333
.50
.03
.00
.02
.25
.02
.88
.51
.02
a. Dependent Variable: BONUS
452 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
115.64
2139157.50
699323.44
187890.098
226
-3.721
7.663
.000
1.000
226
44368.375
605225.563
100618.076
66954.661
226
270846.13
1861245696.00
8938444.09
123761437.322
226
Residual
-1275313.500
1779743.875
.000
594368.618
226
Std.
-2.107
2.941
.000
.982
226
-2.928
3.154
-.006
1.017
226
Deleted
-
2295182.750
-
123809653.416
226
Residual
1861245696.000
Stud.
-2.981
3.222
-.004
1.022
226
.214
224.004
7.965
19.318
226
.000
1050824.875
4649.678
69899.832
226
.001
.996
.035
.086
226
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value
Residual Stud. Residual 8239120.649
Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: BONUS
453 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
454 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
455 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
456 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
457 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
458 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
459 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 2.7 NYSE MEDIUM SIZE COMPANIES (SALARY VS. ROA, ROE, EPS, NPM, CSO, BVCSO, AND MVCSO) Descriptive Statistics Mean
Std. Deviation
N
SALARY
692997.23
208381.176
237
ROA
-.006225
.3544635
237
ROE
-.175945
2.4061468
237
EPS
.4049
4.74236
237
CFPS
2.3276
2.64711
237
NPM
41090995.78
237588097.102
237
CS
98756359.32
110978199.656
237
41912425.72
182451169.304
237
2034320805.54
3180355377.566
237
OUTSTANDING BOOK VALUE OF CS OUTSTANDING MARKET VALUE OF CS OUTSTANDING Model Summary Model
R
b
R
Adjusted
Std. Error of
Change Statistics
Square
R
the Estimate
R
F
Square
Change
Square
Durbindf1
df2
Sig. F
Watson
Change
Change 1
.283
a
.080
.048
203361.975
.080
2.474
8
228
.014
1.027
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VAUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: SALARY
460 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations SALARY
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
SALARY
1.000
.005
.015
.103
.142
.118
.192
.040
.194
ROA
.005
1.000
.149
.184
.076
.261
.019
.092
.078
ROE
.015
.149
1.000
.389
.175
.222
.040
.058
.112
EPS
.103
.184
.389
1.000
.115
.548
-.075
.082
.162
CFPS
.142
.076
.175
.115
1.000
.169
-.061
.060
.247
NPM
.118
.261
.222
.548
.169
1.000
.060
.076
.337
CSO
.192
.019
.040
-.075
-.061
.060
1.000
-.054
.465
BVCSO
.040
.092
.058
.082
.060
.076
-.054
1.000
.116
MVCSO
.194
.078
.112
.162
.247
.337
.465
.116
1.000
Sig.
SALARY
.
.468
.410
.057
.014
.035
.001
.270
.001
(1-tailed)
ROA
.468
.
.011
.002
.121
.000
.388
.079
.117
ROE
.410
.011
.
.000
.003
.000
.270
.187
.043
EPS
.057
.002
.000
.
.039
.000
.123
.105
.006
CFPS
.014
.121
.003
.039
.
.005
.177
.177
.000
NPM
.035
.000
.000
.000
.005
.
.179
.122
.000
CSO
.001
.388
.270
.123
.177
.179
.
.206
.000
BVCSO
.270
.079
.187
.105
.177
.122
.206
.
.038
MVCSO
.001
.117
.043
.006
.000
.000
.000
.038
.
SALARY
237
237
237
237
237
237
237
237
237
ROA
237
237
237
237
237
237
237
237
237
ROE
237
237
237
237
237
237
237
237
237
EPS
237
237
237
237
237
237
237
237
237
CFPS
237
237
237
237
237
237
237
237
237
NPM
237
237
237
237
237
237
237
237
237
CSO
237
237
237
237
237
237
237
237
237
BVCSO
237
237
237
237
237
237
237
237
237
MVCSO
237
237
237
237
237
237
237
237
237
Pearson Correlation
N
461 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
818571499743.994
8
102321437467.999
2.474
.014
Residual
9429189148481.690
228
41356092756.499
Total
10247760648225.700
236
a
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VALUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: SALARY
Coefficients Model
a
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
27.807
.000
B
Std. Error
Beta
(Constant)
620853.720
22327.017
ROA
-19173.518
39002.267
-.033
-.492
.623
ROE
-5803.914
6077.285
-.067
-.955
.341
EPS
4676.592
3576.794
.106
1.307
.192
CFPS
10657.949
5347.256
.135
1.993
.047
NPM
.000
.000
.029
.353
.724
CSO
.000
.000
.187
2.493
.013
BVCSO
.000
.000
.032
.489
.625
MVCSO
.000
.000
.053
.660
.510
a. Dependent Variable: SALARY
462 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
95.0% Confidence Interval
Correlations
Collinearity
for B Lower Bound
Statistics Upper
Zero-order
Partial
Part
Tolerance
VIF
.012
-.031
-
.302
3.311
Bound (Constant)
377614.263
738766.560
ROA
-
1333302.790
2136118.174
.030
ROE
-91.651
180.278
.075
.044
.042
.895
1.117
EPS
-48850.419
109520.747
.054
.051
.049
.290
3.454
CFPS
-52232.750
50944.951
-.002
-.002
-
.532
1.881
.002 NPM
.000
.001
.142
.060
.057
.435
2.297
CSO
-.001
.001
.240
.021
.020
.201
4.965
BVCSO
.000
.000
.270
.103
.099
.202
4.941
MVCSO
.000
.000
.211
.003
.003
.443
2.258
a. Dependent Variable: SALARY
463 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations Model
a
MVCS
CSO
CFP
O Correlations
MVCS
ROA
BVCSO
EPS
ROE
NPM
S
1.000
.034
-.135
.022
-.270
-.036
-.507
-.251
CSO
.034
1.000
-.074
-.078
-.027
-.021
-.025
-.188
CFPS
-.135
-.074
1.000
-.023
.000
-.023
.113
.011
ROA
.022
-.078
-.023
1.000
-.145
-.332
-.085
.026
BVCSO
-.270
-.027
.000
-.145
1.000
.042
.202
-.052
EPS
-.036
-.021
-.023
-.332
.042
1.000
.145
-.482
ROE
-.507
-.025
.113
-.085
.202
.145
1.00
.020
O
0 NPM
-.251
-.188
.011
.026
-.052
-.482
.020
1.00
Covariance
MVCS
.000
.007
.000
.001
-.008
-.001
.000
.000
s
O .007
1521176862.92
-.213
-
-5666423.846
-2915562.206
-.137
-.523
0
CSO
9
18504341.72 2
CFPS
.000
-.213
.000
-.010
.000
-.006
.000
.000
ROA
.001
-18504341.722
-.010
36933395.26
-4723649.150
-7213605.181
-.073
.011
28593147.53
811702.861
.152
-.020
12793456.32
.073
-.123
9 BVCSO
-.008
-5666423.846
.000
-4723649.150
8 EPS
-.001
-2915562.206
-.006
-7213605.181
811702.861
5 ROE
.000
-.137
.000
-.073
.152
.073
.000
.000
NPM
.000
-.523
.000
.011
-.020
-.123
.000
.000
a. Dependent Variable: SALARY
Collinearity Diagnostics Dimensio
Eigenvalu
a
Conditio
Variance Proportions
464 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
n
e
n Index
Variance Proportions (Constan
RO
RO
EP
CFP
NP
CS
BVCS
MVCS
t)
A
E
S
S
M
O
O
O
1
3.015
1.000
.02
.00
.00
.01
.03
.02
.02
.01
.03
2
1.786
1.299
.01
.06
.10
.10
.00
.06
.02
.00
.00
3
.950
1.781
.00
.18
.03
.02
.00
.01
.01
.67
.00
4
.875
1.856
.00
.57
.14
.02
.00
.02
.01
.22
.00
5
.774
1.974
.00
.14
.52
.06
.02
.19
.01
.01
.00
6
.626
2.194
.04
.01
.04
.01
.37
.00
.15
.04
.11
7
.442
2.613
.13
.02
.03
.44
.12
.18
.09
.00
.16
8
.342
2.969
.10
.02
.08
.29
.03
.53
.05
.01
.43
9
.191
3.973
.69
.00
.06
.04
.43
.00
.65
.03
.26
a. Dependent Variable: SALARY
Residuals Statistics
a
465 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Minimum
Maximum
Mean
Std. Deviation
N
513612.22
947908.88
692997.23
58894.170
237
-3.046
4.328
.000
1.000
237
13999.171
194025.359
29494.914
26523.630
237
530250.25
1405295.38
696136.96
76024.920
237
Residual
-596605.563
608569.125
.000
199885.445
237
Std.
-2.934
2.993
.000
.983
237
-2.946
3.017
-.004
.993
237
-705295.375
618488.750
-3139.735
208553.269
237
-2.997
3.072
-.003
.999
237
.123
213.832
7.966
23.713
237
.000
1.217
.007
.079
237
.001
.906
.034
.100
237
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value
Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: SALARY
466 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
467 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
468 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
469 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
470 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
471 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 2.8 NYSE MEDIUM SIZE COMPANIES (BONUS VS. ROA, ROE, EPS, NPM, CSO, BVCSO, AND MVCSO) Descriptive Statistics Mean
Std. Deviation
N
SALARY
304631.01
394004.118
234
ROA
-.007339
.3565083
234
ROE
-.183571
2.4202224
234
EPS
.3332
4.64693
234
CFPS
2.3347
2.65593
234
NPM
42068239.32
239868011.426
234
CS
98910831.43
111299381.931
234
44163179.04
184423684.729
234
2057549094.70
3189011439.668
234
OUTSTANDING BOOK VALUE OF CS OUTSTANDING MARKET VALUE OF CS OUTSTANDING Model Summary Model
R
b
R
Adjusted
Std. Error of
Change Statistics
Square
R
the Estimate
R
F
Square
Change
Square
Durbindf1
df2
Sig. F
Watson
Change
Change 1
.416
a
.173
.144
364583.991
.173
5.890
8
225
.000
1.303
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VAUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: BONUS
472 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations BONUS
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
BONUS
1.000
.117
.065
-.008
.029
.230
.180
.129
-.015
ROA
.117
1.000
.148
.186
.078
.260
.020
.094
.079
ROE
.065
.148
1.000
.397
.176
.221
.041
.060
.113
EPS
-.008
.186
.397
1.000
.102
.561
-.066
.091
.173
CFPS
.029
.078
.176
.102
1.000
.172
-.056
.065
.250
NPM
.230
.260
.221
.561
.172
1.000
.062
.084
.341
CSO
.180
.020
.041
-.066
-.056
.062
1.000
-.051
.466
BVCSO
.129
.094
.060
.091
.065
.084
-.051
1.000
.120
MVCSO
-.015
.079
.113
.173
.250
.341
.466
.120
1.000
Sig.
BONUS
.
.037
.160
.450
.328
.000
.003
.024
.411
(1-tailed)
ROA
.037
.
.012
.002
.118
.000
.382
.077
.114
ROE
.160
.012
.
.000
.003
.000
.267
.182
.043
EPS
.450
.002
.000
.
.060
.000
.159
.083
.004
CFPS
.328
.118
.003
.060
.
.004
.198
.161
.000
NPM
.000
.000
.000
.000
.004
.
.171
.100
.000
CSO
.003
.382
.267
.159
.198
.171
.
.218
.000
BVCSO
.024
.077
.182
.083
.161
.100
.218
.
.034
MVCSO
.411
.114
.043
.004
.000
.000
.000
.034
.
BONUS
234
234
234
234
234
234
234
234
234
ROA
234
234
234
234
234
234
234
234
234
ROE
234
234
234
234
234
234
234
234
234
EPS
234
234
234
234
234
234
234
234
234
CFPS
234
234
234
234
234
234
234
234
234
NPM
234
234
234
234
234
234
234
234
234
CSO
234
234
234
234
234
234
234
234
234
BVCSO
234
234
234
234
234
234
234
234
234
MVCSO
234
234
234
234
234
234
234
234
234
Pearson Correlation
N
473 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
6263409746000.940
8
782926218250.117
5.890
.000
Residual
29907334382593.000
225
132921486144.858
Total
36170744128593.900
233
a
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VALUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: BONUS
Coefficients Model
a
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
5.683
.000
B
Std. Error
Beta
(Constant)
228577.389
40221.049
ROA
52041.459
69949.738
.047
.744
.458
ROE
9531.705
10955.511
.059
.870
.385
EPS
-17205.764
6684.998
-.203
-2.574
.011
CFPS
6946.223
9634.290
.047
.721
.472
NPM
.001
.000
.375
4.792
.000
CSO
.001
.000
.281
3.919
.000
BVCSO
.000
.000
.152
2.466
.014
MVCSO
.000
.000
-.279
-3.623
.000
a. Dependent Variable: BONUS
474 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
95.0% Confidence Interval
Correlations
Collinearit
for B
y Statistics
Lower Bound
Upper
Zero-order
Partial
Part
Tolerance
VIF
.117
.050
.045
.917
1.09
Bound (Constan
149319.261
307835.516
-85798.935
189881.852
t) ROA
0 ROE
-12056.823
31120.233
.065
.058
.053
.811
1.23 2
EPS
-30378.977
-4032.551
-.008
-.169
-.156
.591
1.69 2
CFPS
-12038.757
25931.203
.029
.048
.044
.871
1.14 8
NPM
.000
.001
.230
.304
.290
.598
1.67 1
CSO
.000
.001
.180
.253
.238
.717
1.39 4
BVCSO
.000
.001
.129
.162
.150
.962
1.03 9
MVCSO
.000
.000
-.015
-.235
-.220
.621
1.61 0
a. Dependent Variable: BONUS
475 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model Correlations
Covariances
MVCSO
CSO
CFPS
ROA
BVCSO
EPS
ROE
NPM
MVCSO
1.000
.034
-.134
.025
-.270
-.043
-.509
-.245
CSO
.034
1.000
-.074
-.077
-.028
-.020
-.025
-.186
CFPS
-.134
-.074
1.000
-.020
-.004
-.028
.111
.008
ROA
.025
-.077
-.020
1.000
-.154
-.345
-.086
.041
BVCSO
-.270
-.028
-.004
-.154
1.000
.068
.202
-.067
EPS
-.043
-.020
-.028
-.345
.068
1.000
.144
-.496
ROE
-.509
-.025
.111
-.086
.202
.144
1.000
.017
NPM
-.245
-.186
.008
.041
-.067
-.496
.017
1.000
MVCSO
.000
.023
.000
.003
-.025
-.003
.000
.000
CSO
.023
4892965862.499
-.679
-59031864.038
-
-9196701.090
-.444
-1.671
CFPS
.000
-.679
.000
-.029
-.005
-.025
.000
.000
ROA
.003
-59031864.038
-.029
120023213.205
-
-25274387.596
-.239
.058
18722437.813
16291675.625 BVCSO
-.025
-18722437.813
-.005
-16291675.625
92819552.487
4358315.031
.493
-.083
EPS
-.003
-9196701.090
-.025
-25274387.596
4358315.031
44689202.626
.244
-.427
ROE
.000
-.444
.000
-.239
.493
.244
.000
.000
NPM
.000
-1.671
.000
.058
-.083
-.427
.000
.000
a. Dependent Variable: BONUS
476 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics Dimension
a
Eigenvalue
Condition Index
Variance Proportions (Constant)
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
1
3.026
1.000
.02
.00
.00
.01
.03
.02
.02
.01
.03
2
1.803
1.295
.01
.06
.10
.10
.00
.06
.02
.00
.00
3
.945
1.790
.00
.21
.04
.02
.00
.01
.01
.63
.00
4
.873
1.862
.00
.55
.13
.02
.00
.02
.01
.26
.00
5
.775
1.976
.00
.13
.51
.06
.02
.18
.01
.01
.00
6
.619
2.212
.03
.00
.04
.01
.38
.00
.16
.04
.10
7
.434
2.640
.16
.02
.03
.41
.09
.16
.07
.00
.19
8
.335
3.006
.08
.02
.09
.33
.03
.56
.05
.01
.40
9
.191
3.980
.68
.00
.06
.05
.43
.00
.64
.03
.27
a. Dependent Variable: BONUS
477 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
-519834.75
1197814.25
304631.01
163956.052
234
-5.029
5.448
.000
1.000
234
25334.555
347906.094
53171.656
47905.608
234
-823392.50
1119727.75
298540.40
167715.181
234
Residual
-568309.188
1031677.313
.000
358270.370
234
Std.
-1.559
2.830
.000
.983
234
-1.750
2.923
.007
1.013
234
-822612.500
1548879.250
6090.610
390547.577
234
-1.758
2.973
.009
1.018
234
.129
211.175
7.966
23.842
234
.000
1.459
.014
.101
234
.001
.906
.034
.102
234
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value
Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: BONUS
478 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
479 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
480 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
481 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
482 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
483 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
484 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 2.9 TSX LARGE SIZE COMPANIES (SALARY VS. ROA, ROE, EPS, NPM, CSO, BVCSO, AND MVCSO) Descriptive Statistics Mean
Std. Deviation
N
SALARY
945400.53
418877.249
233
ROA
.089918
.5236883
233
ROE
.135557
.1502165
233
EPS
3.1281
11.35049
233
CFPS
8.5709
28.73189
233
NPM
892281030.04
1206031503.549
233
CS
453432149.95
647699887.438
233
2629921905.58
4257629532.022
233
18071723084.76
30708429638.784
233
OUTSTANDING BOOK VALUE OF CS OUTSTANDING MARKET VALUE OF CS OUTSTANDING Model Summary Model
R
b
R
Adjusted
Std. Error of
Change Statistics
Square
R
the Estimate
R
F
Square
Change
Square
Durbindf1
df2
Sig. F
Watson
Change
Change 1
.480
a
.230
.203
373950.978
.230
8.387
8
224
.000
.705
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VALUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: SALARY
485 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations SALARY
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
SALARY
1.000
.025
.186
-.100
-.008
.427
.267
.283
.263
ROA
.025
1.000
.069
-.007
-.017
-.012
-.021
-.044
.012
ROE
.186
.069
1.000
.139
-.056
.325
.019
-.109
.153
EPS
-.100
-.007
.139
1.000
.137
.062
-.064
-.052
-.009
CFPS
-.008
-.017
-.056
.137
1.000
-.074
-.169
-.104
-.092
NPM
.427
-.012
.325
.062
-.074
1.000
.383
.405
.534
CSO
.267
-.021
.019
-.064
-.169
.383
1.000
.459
.334
BVCSO
.283
-.044
-.109
-.052
-.104
.405
.459
1.000
.384
MVCSO
.263
.012
.153
-.009
-.092
.534
.334
.384
1.000
Sig.
SALARY
.
.353
.002
.064
.454
.000
.000
.000
.000
(1-tailed)
ROA
.353
.
.148
.458
.400
.426
.374
.253
.427
ROE
.002
.148
.
.017
.196
.000
.384
.049
.010
EPS
.064
.458
.017
.
.018
.174
.167
.216
.445
CFPS
.454
.400
.196
.018
.
.129
.005
.057
.081
NPM
.000
.426
.000
.174
.129
.
.000
.000
.000
CSO
.000
.374
.384
.167
.005
.000
.
.000
.000
BVCSO
.000
.253
.049
.216
.057
.000
.000
.
.000
MVCSO
.000
.427
.010
.445
.081
.000
.000
.000
.
SALARY
233
233
233
233
233
233
233
233
233
ROA
233
233
233
233
233
233
233
233
233
ROE
233
233
233
233
233
233
233
233
233
EPS
233
233
233
233
233
233
233
233
233
CFPS
233
233
233
233
233
233
233
233
233
NPM
233
233
233
233
233
233
233
233
233
CSO
233
233
233
233
233
233
233
233
233
BVCSO
233
233
233
233
233
233
233
233
233
MVCSO
233
233
233
233
233
233
233
233
233
Pearson Correlation
N
486 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
9382280076167.430
8
1172785009520.930
8.387
.000
Residual
31324010733328.700
224
139839333630.932
Total
40706290809496.100
232
a
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VALUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: SALARY
Coefficients Model
a
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
18.308
.000
B
Std. Error
Beta
(Constant)
748993.927
40909.859
ROA
22850.839
47068.354
.029
.485
.628
ROE
319302.268
182073.482
.115
1.754
.081
EPS
-4894.605
2213.980
-.133
-2.211
.028
CFPS
1012.556
877.689
.069
1.154
.250
NPM
.000
.000
.317
4.058
.000
CSO
.000
.000
.088
1.281
.202
BVCSO
.000
.000
.127
1.753
.081
MVCSO
.000
.000
.003
.039
.969
a. Dependent Variable: SALARY
487 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
95.0% Confidence Interval
Correlations
Collinearity
for B Lower Bound
Statistics Upper
Zero-order
Partial
Part
Tolerance
VIF
Bound (Constant)
668376.511
829611.343
ROA
-69902.577
115604.254
.025
.032
.028
.992
1.008
ROE
-39493.732
678098.268
.186
.116
.103
.806
1.241
EPS
-9257.498
-531.711
-.100
-.146
-
.954
1.048
.130 CFPS
-717.028
2742.140
-.008
.077
.068
.948
1.055
NPM
.000
.000
.427
.262
.238
.562
1.780
CSO
.000
.000
.267
.085
.075
.721
1.387
BVCSO
.000
.000
.283
.116
.103
.658
1.519
MVCSO
.000
.000
.263
.003
.002
.672
1.489
a. Dependent Variable: SALARY
488 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations Model
a
MVCS
BVCS
O
CFPS
EPS
ROE
NPM
CSO
ROA
O
1.000
.026
-.029
.027
-.038
-.090
-.175
-.383
CFPS
.026
1.000
.014
-.135
-.116
.046
.015
-.058
EPS
-.029
.014
1.000
.015
-.067
.007
.026
.030
ROE
.027
-.135
.015
1.000
.075
.124
.035
-.024
NPM
-.038
-.116
-.067
.075
1.000
.028
.252
-.348
CSO
-.090
.046
.007
.124
.028
1.00
-.309
-.181
1.00
-.251
Correlation
MVCS
s
O
0 ROA
-.175
.015
.026
.035
.252
-.309
0 BVCS
-.383
-.058
.030
-.024
-.348
-.181
-.251
1.000
.000
.000
-.001
.000
-.007
.000
.000
.000
CFPS
.000
4901707.719
1483556.688
-262846.062
-46827133.926
.005
.000
-.003
EPS
-.001
1483556.688
2215429992.7
603745.076
-572945790.838
.015
.009
.038
ROE
.000
-262846.062
603745.076
770338.384
11969500.251
.005
.000
-.001
NPM
-.007
-
-
11969500.25
33150752951.7
.226
.326
-1.718
46827133.92
572945790.83
1
84
6
8
O Covariance
MVCS
s
O
18
CSO
.000
.005
.015
.005
.226
.000
.000
.000
ROA
.000
.000
.009
.000
.326
.000
.000
.000
BVCS
.000
-.003
.038
-.001
-1.718
.000
.000
.000
O a. Dependent Variable: SALARY
489 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics
a
Dimensio
Eigenvalu
Conditio
n
e
n Index
Variance Proportions (Constan
RO
RO
EP
CFP
NP
CS
BVCS
MVCS
t)
A
E
S
S
M
O
O
O
1
3.860
1.000
.02
.00
.02
.01
.00
.02
.02
.02
.02
2
1.247
1.759
.01
.02
.02
.22
.26
.00
.03
.03
.02
3
.993
1.972
.00
.85
.01
.03
.05
.00
.00
.01
.00
4
.818
2.172
.00
.01
.03
.41
.54
.00
.00
.02
.00
5
.672
2.396
.02
.10
.26
.32
.00
.01
.03
.14
.00
6
.524
2.713
.09
.00
.01
.00
.02
.06
.20
.02
.48
7
.356
3.294
.04
.00
.02
.01
.03
.00
.67
.54
.05
8
.313
3.509
.27
.01
.01
.00
.03
.55
.01
.01
.40
9
.217
4.216
.55
.00
.62
.00
.06
.35
.05
.22
.03
a. Dependent Variable: SALARY
490 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
261199.47
1608194.63
945400.53
201099.136
233
-3.402
3.296
.000
1.000
233
26689.258
372438.938
55100.550
48740.584
233
-190210.61
13588861.00
1003287.76
859052.673
233
Residual
-936499.563
1109632.250
.000
367446.986
233
Std.
-2.504
2.967
.000
.983
233
-3.036
2.989
-.016
1.026
233
-12638861.000
1125681.250
-57887.235
916505.897
233
-3.094
3.043
-.015
1.034
233
.186
229.132
7.966
24.245
233
.000
125.900
.551
8.248
233
.001
.988
.034
.105
233
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value
Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: SALARY
491 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
492 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
493 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
494 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
495 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
496 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 2.10 TSX LARGE SIZE COMPANIES (BONUS VS. ROA, ROE, EPS, NPM, CSO, BVCSO, AND MVCSO) Descriptive Statistics Mean
Std. Deviation
N
SALARY
1179186.17
990954.187
220
ROA
.089300
.5386533
220
ROE
.131503
.1521625
220
EPS
3.1077
11.66812
220
CFPS
8.9915
29.29669
220
NPM
897064245.45
1209632924.907
220
CS
461925289.30
656731654.030
220
2574136031.82
4328987967.163
220
18255441210.27
31205042384.301
220
OUTSTANDING BOOK VALUE OF CS OUTSTANDING MARKET VALUE OF CS OUTSTANDING Model Summary Model
R
b
R
Adjusted
Std. Error of
Change Statistics
Square
R
the Estimate
R
F
Square
Change
Square
Durbindf1
df2
Sig. F
Watson
Change
Change 1
.592
a
.350
.325
813861.366
.350
14.210
8
211
.000
1.334
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VALUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: BONUS
497 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations BONUS
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
BONUS
1.000
-.011
.130
-.057
-.015
.527
.336
.425
.340
ROA
-.011
1.000
.065
-.007
-.018
-.021
-.023
-.042
.010
ROE
.130
.065
1.000
.140
-.049
.318
.021
-.108
.154
EPS
-.057
-.007
.140
1.000
.139
.057
-.062
-.053
-.011
CFPS
-.015
-.018
-.049
.139
1.000
-.080
-.178
-.107
-.098
NPM
.527
-.021
.318
.057
-.080
1.000
.388
.382
.522
CSO
.336
-.023
.021
-.062
-.178
.388
1.000
.453
.327
BVCSO
.425
-.042
-.108
-.053
-.107
.382
.453
1.000
.369
MVCSO
.340
.010
.154
-.011
-.098
.522
.327
.369
1.000
Sig.
BONUS
.
.438
.027
.200
.412
.000
.000
.000
.000
(1-tailed)
ROA
.438
.
.168
.457
.395
.381
.367
.269
.443
ROE
.027
.168
.
.019
.236
.000
.376
.055
.011
EPS
.200
.457
.019
.
.019
.201
.180
.218
.436
CFPS
.412
.395
.236
.019
.
.119
.004
.056
.074
NPM
.000
.381
.000
.201
.119
.
.000
.000
.000
CSO
.000
.367
.376
.180
.004
.000
.
.000
.000
BVCSO
.000
.269
.055
.218
.056
.000
.000
.
.000
MVCSO
.000
.443
.011
.436
.074
.000
.000
.000
.
BONUS
220
220
220
220
220
220
220
220
220
ROA
220
220
220
220
220
220
220
220
220
ROE
220
220
220
220
220
220
220
220
220
EPS
220
220
220
220
220
220
220
220
220
CFPS
220
220
220
220
220
220
220
220
220
NPM
220
220
220
220
220
220
220
220
220
CSO
220
220
220
220
220
220
220
220
220
BVCSO
220
220
220
220
220
220
220
220
220
MVCSO
220
220
220
220
220
220
220
220
220
Pearson Correlation
N
498 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
75295715949884.500
8
9411964493735.560
14.210
.000
Residual
139760138134691.000
211
662370322913.227
Total
215055854084575.000
219
a
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VALUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: BONUS
Coefficients Model
a
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
7.164
.000
B
Std. Error
Beta
(Constant)
647195.921
90343.878
ROA
13053.270
102504.246
.007
.127
.899
ROE
266173.382
399820.955
.041
.666
.506
EPS
-6540.714
4824.500
-.077
-1.356
.177
CFPS
2381.841
1930.830
.070
1.234
.219
NPM
.000
.000
.392
5.378
.000
CSO
.000
.000
.074
1.138
.257
BVCSO
.000
.000
.242
3.592
.000
MVCSO
.000
.000
.021
.317
.752
a. Dependent Variable: BONUS
499 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
95.0% Confidence Interval
Correlations
Collinearit
for B
y Statistics
Lower Bound
Upper
Zero-order
Partial
Part
Tolerance
VIF
Bound (Constant)
469103.686
825288.156
ROA
-189010.342
215116.883
-.011
.009
.007
.992
1.008
ROE
-521981.931
1054328.695
.130
.046
.037
.817
1.224
EPS
-16051.109
2969.681
-.057
-.093
-.075
.954
1.048
CFPS
-1424.347
6188.030
-.015
.085
.068
.945
1.058
NPM
.000
.000
.527
.347
.298
.580
1.724
CSO
.000
.000
.336
.078
.063
.718
1.392
BVCSO
.000
.000
.425
.240
.199
.679
1.472
MVCSO
.000
.000
.340
.022
.018
.685
1.460
a. Dependent Variable: BONUS
500 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model Correlations
Covariances
MVCSO
CFPS
EPS
ROE
NPM
CSO
ROA
BVCSO
MVCSO
1.000
-.029
.026
.030
-.045
-.084
-.176
-.376
CFPS
-.029
1.000
.014
.017
-.067
.008
.022
.038
EPS
.026
.014
1.000
-.137
-.120
.043
.014
-.053
ROE
.030
.017
-.137
1.000
.065
.131
.031
-.020
NPM
-.045
-.067
-.120
.065
1.000
.030
.237
-.332
CSO
-.084
.008
.043
.131
.030
1.000
-.310
-.201
ROA
-.176
.022
.014
.031
.237
-.310
1.000
-.222
BVCSO
-.376
.038
-.053
-.020
-.332
-.201
-.222
1.000
MVCSO
.000
-.006
.000
.000
-.038
.000
.000
.000
CFPS
-.006
10507120545.325
6827916.362
33635
-
.077
.034
.231
47.76
27530
1
68924. .020
.001
-.015
.025
.001
-.002
1.197
1.462
-7.929
476 EPS
ROE
NPM
.000
.000
-.038
6827916.362
3363547.761
-2753068924.476
23275799.226
-1272768.922
-
-
12727
23180
68.92
6557.7
2
62
37281
50200
04.68
458.81
3
8
-
50200
15985
231806557.762
458.8
67963
18
29.184
CSO
.000
.077
.020
.025
1.197
.000
.000
.000
ROA
.000
.034
.001
.001
1.462
.000
.000
.000
BVCSO
.000
.231
-.015
-.002
-7.929
.000
.000
.000
a. Dependent Variable: BONUS
501 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics Dimension
a
Eigenvalue
Condition Index
Variance Proportions (Constant)
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
1
3.813
1.000
.02
.00
.02
.01
.00
.02
.02
.02
.02
2
1.255
1.743
.01
.02
.02
.22
.25
.00
.03
.04
.02
3
.995
1.958
.00
.86
.01
.03
.04
.00
.00
.01
.00
4
.817
2.160
.00
.01
.03
.41
.53
.00
.00
.02
.00
5
.685
2.359
.02
.09
.26
.32
.00
.01
.03
.16
.00
6
.525
2.696
.09
.01
.02
.00
.03
.05
.18
.02
.52
7
.360
3.253
.03
.00
.04
.00
.03
.00
.66
.57
.03
8
.318
3.462
.28
.01
.01
.00
.04
.58
.00
.01
.37
9
.232
4.055
.55
.00
.59
.00
.07
.33
.09
.16
.04
a. Dependent Variable: BONUS
502 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
48755.68
3305852.75
1179186.17
586358.299
220
-1.928
3.627
.000
1.000
220
59531.543
811032.250
123791.295
108749.435
220
-423849.09
11336792.00
1242645.93
951603.757
220
Residual
-2063748.750
2321985.250
.000
798858.027
220
Std.
-2.536
2.853
.000
.982
220
-2.982
3.146
-.011
1.022
220
-10391792.000
2960627.000
-63459.759
1137659.086
220
-3.039
3.215
-.010
1.029
220
.176
216.485
7.964
23.697
220
.000
17.989
.101
1.224
220
.001
.989
.036
.108
220
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value
Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: BONUS
503 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
504 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
505 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
506 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
507 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
508 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
509 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 2.11 NYSE LARGE SIZE COMPANIES (SALARY VS. ROA, ROE, EPS, NPM, CSO, BVCSO, AND MVCSO) Descriptive Statistics Mean
Std. Deviation
N
SALARY
1011495.09
341672.550
235
ROA
.042960
.0989126
235
ROE
8.844675
151.8543516
235
EPS
-1.7153
49.98012
235
CFPS
5.2061
10.40443
235
NPM
2016124591.49
10917840059.567
235
CS
1135258373.07
2929182961.365
235
4280369048.11
17220871648.092
235
23538173488.56
44900153837.237
235
OUTSTANDING BOOK VALUE OF CS OUTSTANDING MARKET VALUE OF CS OUTSTANDING Model Summary Model
R
b
R
Adjusted
Std. Error of
Change Statistics
Square
R
the Estimate
R
F
Square
Change
Square
Durbindf1
df2
Sig. F
Watson
Change
Change 1
.571
a
.326
.302
285409.381
.326
13.669
8
226
.000
.909
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VALUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: SALARY
510 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations SALARY
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
SALARY
1.000
.108
.012
.207
.158
.159
-.160
.230
.462
ROA
.108
1.000
.061
.166
.016
.189
-.021
-.010
.128
ROE
.012
.061
1.000
.009
.078
-.003
-.021
-.030
-.022
EPS
.207
.166
.009
1.000
-.049
.640
.024
.023
.066
CFPS
.158
.016
.078
-.049
1.000
-.048
-.035
.073
.134
NPM
.159
.189
-.003
.640
-.048
1.000
.481
.135
.330
CSO
-.160
-.021
-.021
.024
-.035
.481
1.000
.294
.220
BVCSO
.230
-.010
-.030
.023
.073
.135
.294
1.000
.634
MVCSO
.462
.128
-.022
.066
.134
.330
.220
.634
1.000
Sig.
SALARY
.
.049
.425
.001
.008
.007
.007
.000
.000
(1-tailed)
ROA
.049
.
.177
.006
.405
.002
.372
.438
.025
ROE
.425
.177
.
.444
.117
.483
.374
.325
.371
EPS
.001
.006
.444
.
.228
.000
.357
.361
.155
CFPS
.008
.405
.117
.228
.
.234
.297
.134
.020
NPM
.007
.002
.483
.000
.234
.
.000
.020
.000
CSO
.007
.372
.374
.357
.297
.000
.
.000
.000
BVCSO
.000
.438
.325
.361
.134
.020
.000
.
.000
MVCSO
.000
.025
.371
.155
.020
.000
.000
.000
.
SALARY
235
235
235
235
235
235
235
235
235
ROA
235
235
235
235
235
235
235
235
235
ROE
235
235
235
235
235
235
235
235
235
EPS
235
235
235
235
235
235
235
235
235
CFPS
235
235
235
235
235
235
235
235
235
NPM
235
235
235
235
235
235
235
235
235
CSO
235
235
235
235
235
235
235
235
235
BVCSO
235
235
235
235
235
235
235
235
235
MVCSO
235
235
235
235
235
235
235
235
235
Pearson Correlation
N
511 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
8907566513493.000
8
1113445814186.620
13.669
.000
Residual
18409624284856.100
226
81458514534.762
Total
27317190798349.100
234
a
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VALUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: SALARY
Coefficients Model
a
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
38.099
.000
B
Std. Error
Beta
(Constant)
943897.299
24774.782
ROA
10134.677
195331.904
.003
.052
.959
ROE
18.262
123.576
.008
.148
.883
EPS
1164.724
557.226
.170
2.090
.038
CFPS
2963.081
1825.578
.090
1.623
.106
NPM
.000
.000
.022
.225
.822
CSO
.000
.000
-.276
-3.767
.000
BVCSO
.000
.000
-.023
-.302
.763
MVCSO
.000
.000
.506
6.399
.000
a. Dependent Variable: SALARY
512 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
95.0% Confidence Interval
Correlations
Collinearity
for B Lower Bound
Statistics Upper
Zero-order
Partial
Part
Tolerance
VIF
Bound (Constant)
895078.189
992716.410
ROA
-374770.012
395039.367
.108
.003
.003
.933
1.072
ROE
-225.247
261.771
.012
.010
.008
.989
1.012
EPS
66.701
2262.746
.207
.138
.114
.449
2.228
CFPS
-634.249
6560.412
.158
.107
.089
.965
1.036
NPM
.000
.000
.159
.015
.012
.304
3.292
CSO
.000
.000
-.160
-.243
-
.556
1.798
.521
1.919
.477
2.097
.206 BVCSO
.000
.000
.230
-.020
.016
MVCSO
.000
.000
.462
.392
.349
a. Dependent Variable: SALARY
513 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model Correlations
BVCS MVCSO
MVCSO
CFPS
EPS
ROE
NPM
CSO
ROA
O
1.000
.022
.268
-.132
-.111
.211
-
-.404
.651 CFPS
.022
1.000
-.003
-.081
-.060
.006
.010
-.001
EPS
.268
-.003
1.000
.000
-.035
.447
-
-.732
ROE
-.132
-.081
.000
1.000
-.004
.015
.018
.055
NPM
-.111
-.060
-.035
-.004
1.000
.084
.075
-.098
CSO
.211
.006
.447
.015
.084
1.000
-
-.622
ROA
-.651
.010
-.201
.018
.075
-.326
BVCSO
-.404
-.001
-.732
.055
-.098
-.622
.283
1.000
MVCSO
.000
.000
.000
.000
-.013
.000
.000
.000
CFPS
.000
15271.082
-182.974
-18358.472
-1452639.214
.000
.000
.000
EPS
.000
-182.974
310500.842
-476.115
-3797032.653
.002
.000
-.001
ROE
.000
-18358.472
-476.115
3332734.156
-1565274.971
.000
.000
.000
NPM
-.013
-1452639.214
-3797032.653
-1565274.971
38154552676.798
.140
.022
-.059
CSO
.000
.000
.002
.000
.140
.000
.000
.000
ROA
.000
.000
.000
.000
.022
.000
.000
.000
BVCSO
.000
.000
-.001
.000
-.059
.000
.000
.000
.201
.326 1.00
.283
0 Covariances
a. Dependent Variable: SALARY
514 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics
a
Dimensio
Eigenvalu
Conditio
n
e
n Index
Variance Proportions (Constan
RO
RO
EP
CFP
NP
CS
BVCS
MVCS
t)
A
E
S
S
M
O
O
O
1
2.852
1.000
.03
.02
.00
.00
.02
.01
.02
.02
.03
2
1.561
1.352
.03
.00
.00
.12
.06
.06
.00
.01
.00
3
1.177
1.557
.03
.16
.20
.01
.06
.00
.03
.09
.01
4
.938
1.744
.03
.09
.78
.00
.01
.00
.01
.03
.00
5
.808
1.878
.03
.02
.00
.05
.00
.01
.30
.11
.06
6
.744
1.958
.00
.40
.01
.05
.53
.00
.00
.00
.00
7
.437
2.553
.72
.27
.00
.04
.31
.00
.06
.01
.01
8
.339
2.899
.05
.03
.00
.16
.00
.11
.06
.39
.44
9
.142
4.486
.09
.00
.00
.56
.00
.80
.51
.33
.44
a. Dependent Variable: SALARY
515 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
-12754.85
1797301.13
1011495.09
195106.442
235
-5.250
4.028
.000
1.000
235
19092.875
284575.063
39300.623
39772.858
235
-1726465.25
1825447.00
1007565.02
258465.904
235
Residual
-827702.563
629272.313
.000
280488.160
235
Std.
-2.900
2.205
.000
.983
235
-3.057
2.216
-.002
.997
235
-919759.313
1726466.250
3930.067
311594.900
235
-3.115
2.235
-.003
1.001
235
.051
231.638
7.966
29.554
235
.000
4.036
.022
.264
235
.000
.990
.034
.126
235
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value
Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: SALARY
516 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
517 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
518 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
519 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
520 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
521 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
522 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 2.12 NYSE LARGE SIZE COMPANIES (BONUS VS. ROA, ROE, EPS, NPM, CSO, BVCSO, AND MVCSO) Descriptive Statistics Mean
Std. Deviation
N
SALARY
698427.79
1002631.619
219
ROA
.044625
.1008268
219
ROE
9.484072
157.3091470
219
EPS
-1.3329
52.40193
219
CFPS
6.0769
13.08076
219
NPM
992783789.95
8399655075.607
219
CS
877523476.11
2237321446.774
219
3193301266.24
15843574985.314
219
20268959348.21
39149463196.164
219
OUTSTANDING BOOK VALUE OF CS OUTSTANDING MARKET VALUE OF CS OUTSTANDING Model Summary Model
R
b
R
Adjusted
Std. Error of
Change Statistics
Square
R
the Estimate
R
F
Square
Change
Square
Durbindf1
df2
Sig. F
Watson
Change
Change 1
.592
a
.350
.325
813861.366
.350
14.210
8
211
.000
1.334
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VALUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: BONUS
523 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations BONUS
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
BONUS
1.000
.199
-.042
.059
-.015
.126
-.070
-.104
.117
ROA
.199
1.000
.061
.163
-.011
.269
-.017
.002
.159
ROE
-.042
.061
1.000
.009
.060
.003
-.022
-.029
-.021
EPS
.059
.163
.009
1.000
-.027
.860
.033
.021
.081
CFPS
-.015
-.011
.060
-.027
1.000
.055
.008
.072
.118
NPM
.126
.269
.003
.860
.055
1.000
.060
.117
.389
CSO
-.070
-.017
-.022
.033
.008
.060
1.000
.356
.252
BVCSO
-.104
.002
-.029
.021
.072
.117
.356
1.000
.565
MVCSO
.117
.159
-.021
.081
.118
.389
.252
.565
1.000
Sig.
BONUS
.
.002
.270
.191
.415
.031
.150
.062
.042
(1-tailed)
ROA
.002
.
.186
.008
.435
.000
.404
.486
.009
ROE
.270
.186
.
.449
.187
.480
.374
.332
.381
EPS
.191
.008
.449
.
.346
.000
.312
.376
.115
CFPS
.415
.435
.187
.346
.
.207
.451
.143
.041
NPM
.031
.000
.480
.000
.207
.
.189
.042
.000
CSO
.150
.404
.374
.312
.451
.189
.
.000
.000
BVCSO
.062
.486
.332
.376
.143
.042
.000
.
.000
MVCSO
.042
.009
.381
.115
.041
.000
.000
.000
.
BONUS
219
219
219
219
219
219
219
219
219
ROA
219
219
219
219
219
219
219
219
219
ROE
219
219
219
219
219
219
219
219
219
EPS
219
219
219
219
219
219
219
219
219
CFPS
219
219
219
219
219
219
219
219
219
NPM
219
219
219
219
219
219
219
219
219
CSO
219
219
219
219
219
219
219
219
219
BVCSO
219
219
219
219
219
219
219
219
219
MVCSO
219
219
219
219
219
219
219
219
219
Pearson Correlation
N
524 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
19398861641706.900
8
2424857705213.360
2.549
.011
Residual
199750033891028.000
210
951190637576.324
Total
219148895532735.000
218
a
a. Predictors: (Constant), MARKET VALUE OF CS OUTSTANDING, EPS, ROE, CFPS, NPM, BOOK VALUE OF CS OUTSTANDING, ROA, CS OUTSTANDING b. Dependent Variable: BONUS
Coefficients Model
a
Unstandardized
Standardized
Coefficients
Coefficients
t
Sig.
6.751
.000
B
Std. Error
Beta
(Constant)
588990.533
87239.045
ROA
1577426.787
690563.512
.159
2.284
.023
ROE
-337.457
421.917
-.053
-.800
.425
EPS
-335.243
3049.770
-.018
-.110
.913
CFPS
-1653.070
5135.615
-.022
-.322
.748
NPM
.000
.000
.047
.264
.792
CSO
.000
.000
-.049
-.685
.494
BVCSO
.000
.000
-.210
-2.459
.015
MVCSO
.000
.000
.208
1.983
.049
a. Dependent Variable: BONUS
525 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients Model
a
95.0% Confidence Interval
Correlations
Collinearit
for B
y Statistics
Lower Bound
Upper
Zero-order
Partial
Part
Tolerance
VIF
Bound (Constant)
417014.040
760967.025
ROA
216101.815
2938751.759
.199
.156
.150
.900
1.111
ROE
-1169.193
494.279
-.042
-.055
-.053
.990
1.010
EPS
-6347.330
5676.844
.059
-.008
-.007
.171
5.854
CFPS
-11777.035
8470.894
-.015
-.022
-.021
.967
1.034
NPM
.000
.000
.126
.018
.017
.140
7.140
CSO
.000
.000
-.070
-.047
-.045
.864
1.157
BVCSO
.000
.000
-.104
-.167
-.162
.596
1.677
MVCSO
.000
.000
.117
.136
.131
.396
2.527
a. Dependent Variable: BONUS
526 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model Correlations
BVCS MVCSO
MVCSO
CFPS
EPS
ROE
NPM
CSO
ROA
O
1.000
.006
.545
-.009
-.021
-.090
-
-.621
.538 CFPS
.006
1.000
-.018
-.067
-.066
.009
.016
.019
EPS
.545
-.018
1.000
.116
.116
-.062
-
-.908
ROE
-.009
-.067
.116
1.000
.051
.018
NPM
-.021
-.066
.116
.051
1.000
.024
.044
-.196
CSO
-.090
.009
-.062
.018
.024
1.000
-
.056
.188 -
-.113
.035
.245 ROA
-.538
.016
-.188
-.035
.044
-.245
1.00
.216
0 Covariances
BVCSO
-.621
.019
-.908
-.113
-.196
.056
.216
1.000
MVCSO
.000
.000
.004
.000
-.038
.000
.000
.000
CFPS
.000
178014.121
-23122.169
-145063.526
-19185513.067
.000
.000
.000
EPS
.004
-23122.169
9301097.279
1813615.406
245315348.481
-.006
-
-.058
.003 ROE
.000
-145063.526
1813615.406
26374537.152
180863051.778
.003
-
-.012
NPM
-.038
-19185513.067
245315348.481
180863051.77
476877963490.73
.525
.163
-2.848
8
2
CSO
.000
.000
-.006
.003
.525
.000
.000
.000
ROA
.000
.000
-.003
-.001
.163
.000
.000
.000
BVCSO
.000
.000
-.058
-.012
-2.848
.000
.000
.000
.001
a. Dependent Variable: BONUS
527 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics Dimension
a
Eigenvalue
Condition Index
Variance Proportions (Constant)
ROA
ROE
EPS
CFPS
NPM
CSO
BVCSO
MVCSO
1
2.762
1.000
.03
.03
.00
.00
.02
.01
.03
.03
.03
2
1.752
1.255
.02
.00
.00
.04
.02
.03
.02
.01
.00
3
1.173
1.535
.05
.11
.20
.00
.08
.00
.05
.12
.01
4
.941
1.713
.03
.05
.79
.00
.02
.00
.02
.05
.00
5
.804
1.854
.00
.37
.00
.00
.55
.00
.01
.00
.00
6
.697
1.991
.04
.04
.00
.01
.00
.00
.65
.10
.06
7
.455
2.464
.49
.38
.00
.00
.27
.00
.11
.06
.07
8
.345
2.828
.30
.00
.00
.04
.01
.01
.10
.53
.31
9
.071
6.245
.04
.03
.00
.90
.01
.95
.00
.10
.51
a. Dependent Variable: BONUS
528 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
-945170.06
2007830.63
698427.79
298304.549
219
-5.510
4.389
.000
1.000
219
67375.727
972440.938
139152.118
140773.590
219
-1720905.00
13513766.00
770592.81
933688.283
219
Residual
-1263942.125
2921673.500
.000
957227.538
219
Std.
-1.296
2.996
.000
.981
219
-1.334
3.005
-.006
.999
219
-13513766.000
2940308.000
-72165.029
1359465.267
219
-1.336
3.065
-.003
1.004
219
.045
215.733
7.963
27.217
219
.000
21.208
.105
1.434
219
.000
.990
.037
.125
219
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value
Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: BONUS
529 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
530 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
531 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
532 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
533 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
534 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
535 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 3.1 TSX SMALL SIZE COMPANIES (SALARY VS. CEO AGE, CEO SHARES OUTSTANDING CEO SHARES VALUE, CEO TENURE, 5% MANAGEMENT AND INDIVIDUAL/INSTITUTIONAL OWNERSHIP) Descriptive Statistics Mean
Std. Deviation
N
SALARY
362844.89
166684.802
238
CEO AGE
51.12
10.626
238
CEO SHARES
1973541.81
3356340.662
238
26862198.63
76142243.316
238
CEO TENURE
8.21
6.402
238
CEO
.05
.228
238
5% MGMT
.31
.561
238
5%
.99
.867
238
OUTSTANDING CEO SHARES VALUE
TURNOVER
INDS./INSTIS.
Model Summary
b
Model
Change Statistics
R 1
.461
a
Adjusted
Std. Error
R
R
R
of the
Square
F
Square
Square
Estimate
Change
Change
df1
.212
.188
150191.710
.212
8.844
7
Sig. F
Durbin-
df2
Change
Watson
230
.000
.802
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: SALARY
536 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
1396529654462.640
7
199504236351.806
8.844
.000
Residual
5188236447891.290
230
22557549773.440
Total
6584766102353.930
237
a
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: SALARY
537 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations
Pearson Correlatio n
Sig. (1tailed)
N
CEO SHARES OUTSTAN DING -.099
CEO SHARE S VALUE .218
CEO TENUR E .097
CEO TURNOVE R -.063
=/> 5% MGM T -.124
=/> 5% INDVS./INSTI S.
SALARY
SALA RY 1.000
CEO AGE .106
CEO AGE
.106
.023
.160
.063
-.090
.137
-.044
CEO SHARES
-.099
1.00 0 .023
1.000
.488
.406
-.136
.599
-.049
CEO SHARES VALUE
.218
.160
.488
1.000
.279
-.082
.353
.044
CEO TENURE
.097
.063
.406
.279
1.000
-.271
.369
-.051
CEO TURNOVER
-.063
.090
-.136
-.082
-.271
1.000
-.099
.045
5% MGMT
-.124
.137
.599
.353
.369
-.099
1.000
-.212
5% INDS./INSTIS.
.309
.044
-.049
.044
-.051
.045
-.212
1.000
SALARY
.
.052
.064
.000
.068
.165
.029
.000
CEO AGE
.052
.
.363
.007
.166
.083
.018
.250
CEO SHARES OUTSTANDING
.064
.363
.
.000
.000
.018
.000
.224
CEO SHARES VALUE
.000
.007
.000
.
.000
.105
.000
.251
CEO TENURE
.068
.166
.000
.000
.
.000
.000
.218
CEO TURNOVER
.165
.083
.018
.105
.000
.
.065
.244
5% MGMT
.029
.018
.000
.000
.000
.065
.
.001
5% INDS./INSTIS.
.000
.250
.224
.251
.218
.244
.001
.
SALARY
238
238
238
238
238
238
238
238
CEO AGE
238
238
238
238
238
238
238
238
CEO SHARES OUTSTANDING
238
238
238
238
238
238
238
238
CEO SHARES VALUE
238
238
238
238
238
238
238
238
CEO TENURE
238
238
238
238
238
238
238
238
CEO TURNOVER
238
238
238
238
238
238
238
238
5% MGMT
238
238
238
238
238
238
238
238
5% INDS./INSTIS.
238
238
238
238
238
238
238
238
.309
538 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Stan dard ized Coef Unstandardized
ficie
95.0% Confidence
Coefficients
nts
Interval for B
Collinearity Correlations
Statistics
Zero Std.
(Constant)
B
Error
236627.9
52575.0
Beta
Lower
Upper
orde
Parti
r
al
Part
ance
VIF
.106
.081
.072
.944
1.060
-
-
-.175
.520
1.925
.099
.194
t
Sig.
Bound
Bound
4.501
.000
133037.
340218.
04
83
549
260
CEO AGE
1163.645
945.120
.074
1.231
.220
-698.555
3025.84
CEO
-.012
.004
-
-2.992
.003
-.020
Toler
6 SHARES
-.004
.243
OUTSTANDI NG CEO
.001
.000
.302
4.395
.000
.000
.001
.218
.278
.257
.724
1.382
3696.520
1749.06
.142
2.113
.036
250.292
7142.74
.097
.138
.124
.759
1.318
-.791
.430
-
52738.1
-
-
-.046
.918
1.089
123472.
41
.063
.052
-
17444.0
-
-
-.071
.575
1.738
72894.0
04
.124
.079
30363.7
76253.2
.309
.289
.268
.935
1.070
75
37
SHARES VALUE CEO TENURE
0
9
CEO
-
44716.0
-
TURNOVER
35367.39
90
.048
2 5% MGMT
924
-
22924.5
-
27725.00
70
.093
-1.209
.228
4
13
5%
53308.50
11645.1
INDS./INSTI
6
10
.277
4.578
.000
S. a. Dependent Variable: SALARY
539 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model
5%
CEO
INDS./IN
SHAR
STIS.
ES
CEO
CEO
OUTSTANDI
VALUE
TURNOVER
CEO AGE
TENURE
NG
1.000
-.102
-.035
.022
-.006
.228
-.053
-.102
1.000
-.015
-.160
-.085
-.069
-.348
-.035
-.015
1.000
.081
.237
-.038
.048
CEO AGE
.022
-.160
.081
1.000
.000
-.130
.132
CEO TENURE
-.006
-.085
.237
.000
1.000
-.160
-.185
5% MGMT
.228
-.069
-.038
-.130
-.160
1.000
-.480
CEO SHARES
-.053
-.348
.048
.132
-.185
-.480
1.000
-.179
-
238426.18
-
60983627.4
-2.487
18245533.70
6
118556.34
85
Correlatio
5%
ns
INDS./INSTIS. CEO SHARES
5% MGMT
CEO SHARES
VALUE CEO TURNOVER
OUTSTANDIN G Covarianc
5%
13560859
es
INDS./INSTIS.
5.837
9 CEO SHARES
9
-.179
.000
-.100
-.023
-.022
-.238
.000
CEO
-
-.100
1999528699.
3417595.0
18542644.
-
8.717
TURNOVER
18245533
773
39
188
39225238.0
VALUE
.709 CEO AGE
238426.1
82 -.023
3417595.039
86
893252.42
63.180
0
-
.504
2812926.95 9
CEO TENURE
-
-.022
118556.3
18542644.18
63.180
8
3059210.5
-
38
6418413.21
49 5% MGMT
60983627
4 -.238
.485 CEO SHARES
-2.487
-1.307
.000
-
-
-
525535907.
39225238.08
2812926.9
6418413.2
356
2
59
14
8.717
.504
-1.307
-44.412
-44.412
.000
OUTSTANDIN G
540 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics
a
Mod el
Variance Proportions
Conditi
CEO
5%
5%
MG
INDS.
MT
/
CE
CEO
SHAR
O
SHARES
ES
CEO
CEO
Eigenva
on
(Consta
AG
OUTSTAND
VALU
TENU
TURNOV
INSTI
lue
Index
nt)
E
ING
E
RE
ER
S.
1
4.382
1.000
.00
.00
.01
.01
.01
.00
.01
.01
2
1.330
1.815
.00
.00
.04
.08
.00
.18
.05
.04
3
.867
2.248
.00
.00
.02
.07
.01
.68
.03
.02
4
.602
2.699
.00
.00
.01
.61
.01
.01
.19
.08
5
.330
3.644
.00
.01
.41
.17
.09
.00
.00
.43
6
.271
4.021
.00
.00
.34
.03
.23
.05
.65
.17
7
.200
4.681
.02
.04
.15
.00
.62
.06
.06
.22
8
.019
15.219
.97
.95
.02
.03
.02
.02
.01
.02
a. Dependent Variable: SALARY
541 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Residuals Statistics
a
Minimum 105713.52
Maximum 649258.69
Mean 362844.89
Std. Deviation 76762.818
N 238
-3.350
3.731
.000
1.000
238
11650.292
69973.992
24804.062
11983.273
238
89807.51
660697.19
362433.63
77957.084
238
380165.938 -2.531
447057.000
.000
147957.065
238
Std. 2.977 Residual Stud. -2.671 3.015 Residual Deleted 459546.656 Residual 423229.500 Stud. -2.707 3.069 Deleted Residual Mahal. .430 50.448 Distance Cook's .000 .101 Distance Centered .002 .213 Leverage Value a. Dependent Variable: SALARY
.000
.985
238
.001
1.001
238
411.255
152778.280
238
.003
1.007
238
6.971
8.141
238
.004
.010
238
.029
.034
238
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
542 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
543 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
544 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
545 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
546 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
547 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 3.2 TSX SMALL SIZE COMPANIES (BONUS VS. CEO AGE, CEO SHARES OUTSTANDING CEO SHARES VALUE, CEO TENURE, 5% MANAGEMENT AND INDIVIDUAL/INSTITUTIONAL OWNERSHIP) Descriptive Statistics Mean
Std. Deviation
N
BONUS
150893.14
154741.497
211
CEO AGE
50.47
10.734
211
CEO SHARES
2119809.38
3523842.335
211
27105267.36
79971421.670
211
CEO TENURE
8.13
6.176
211
CEO
.06
.232
211
5% MGMT
.31
.565
211
5%
1.00
.859
211
OUTSTANDING CEO SHARES VALUE
TURNOVER
INDS./INSTIS.
Model Summary
b
Model
Change Statistics
R 1
.413
a
Adjusted
Std. Error
R
R
R
of the
Square
F
Square
Square
Estimate
Change
Change
df1
.171
.142
143341.274
.171
5.962
7
Sig. F
Durbin-
df2
Change
Watson
203
.000
1.396
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: BONUS
548 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
857451180521.926
7
122493025788.847
5.962
.000
Residual
4170984323291.090
203
20546720804.390
Total
5028435503813.010
210
a
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: BONUS
549 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations
Pearson Correlatio n
Sig. (1tailed)
N
CEO SHARE S VALUE .215
CEO TENUR E .053
CEO TURNOVE R -.123
=/> 5% MGM T -.106
=/> 5% INDVS./INSTI S.
BONUS
BONU S 1.000
CEO AGE .173
CEO SHARES OUTSTAN DING -.140
CEO AGE
.173
1.000
.032
.143
-.040
-.059
.089
.013
CEO SHARES
-.140
.032
1.000
.486
.425
-.146
.620
-.039
CEO SHARES VALUE
.215
.143
.486
1.000
.252
-.083
.339
.073
CEO TENURE
.053
-.040
.425
.252
1.000
-.284
.327
.015
CEO TURNOVER
-.123
-.059
-.146
-.083
-.284
1.000
-.098
.025
5% MGMT
-.106
.089
.620
.339
.327
-.098
1.000
-.174
5% INDS./INSTIS.
.070
.013
-.039
.073
.015
.025
-.174
1.000
BONUS
.
.006
.021
.001
.223
.037
.063
.155
CEO AGE
.006
.
.319
.019
.281
.199
.099
.425
CEO SHARES OUTSTANDING
.021
.319
.
.000
.000
.017
.000
.287
CEO SHARES VALUE
.001
.019
.000
.
.000
.116
.000
.147
CEO TENURE
.223
.281
.000
.000
.
.000
.000
.412
CEO TURNOVER
.037
.199
.017
.116
.000
.
.078
.358
5% MGMT
.063
.099
.000
.000
.000
.078
.
.006
5% INDS./INSTIS.
.155
.425
.287
.147
.412
.358
.006
.
BONUS
211
211
211
211
211
211
211
211
CEO AGE
211
211
211
211
211
211
211
211
CEO SHARES OUTSTANDING
211
211
211
211
211
211
211
211
CEO SHARES VALUE
211
211
211
211
211
211
211
211
CEO TENURE
211
211
211
211
211
211
211
211
CEO TURNOVER
211
211
211
211
211
211
211
211
5% MGMT
211
211
211
211
211
211
211
211
5% INDS./INSTIS.
211
211
211
211
211
211
211
211
.070
550 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Stan dard ized Coef Unstandardized
ficie
95.0% Confidence
Coefficients
nts
Interval for B
Collinearity Correlations
Statistics
Zero Std.
(Constant)
B
Error
48525.97
52529.7
Beta
6
65
Lower
Upper
orde
Parti
r
al
Part
ance
VIF
.173
.147
.136
.960
1.042
-
-
-.226
.490
2.040
.140
.241
t
Sig.
Bound
Bound
.924
.357
-
152099.
55047.9
903
Toler
52 CEO AGE
1997.769
940.502
.139
2.124
.035
143.362
3852.17 5
CEO
-.014
.004
-
SHARES
-3.535
.001
-.022
-.006
.323
OUTSTANDI NG CEO
.001
.000
.340
4.560
.000
.000
.001
.215
.305
.291
.734
1.362
2550.020
1847.12
.102
1.381
.169
-
6192.03
.053
.096
.088
.752
1.330
1091.99
5 -.108
.912
1.096
-.056
.579
1.727
.019
.945
1.058
SHARES VALUE CEO TENURE
7
5 CEO
-
44609.6
-
TURNOVER
75200.10
06
.113
-1.686
.093
0 5% MGMT
5%
-
23020.0
-
20236.06
33
.074
3543.668
12757.5
-
-
163157.
01
.123
.117
-
25152.9
-
-
65625.0
71
.106
.062
-
26893.7
.070
.021
19806.4
82
701 -.879
.380
2 INDS./INSTI
-
94 11842.5 17
S.
.020
.299
.765
45
a. Dependent Variable: BONUS
551 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model
5%
5% MGMT
CEO
INDS./IN
CEO
CEO
STIS.
SHARES
TURNOVE
CEO
OUTSTANDI
VALUE
R
CEO AGE
TENURE
NG
1.000
-.022
-.056
-.034
-.111
.203
-.028
-.022
1.000
.093
.075
-.143
-.091
.061
-.056
.093
1.000
.254
-.057
-.104
-.238
CEO AGE
-.034
.075
.254
1.000
-.007
-.026
.034
CEO TENURE
-.111
-.143
-.057
-.007
1.000
-.057
-.345
5% MGMT
.203
-.091
-.104
-.026
-.057
1.000
-.507
CEO SHARES
-.028
.061
-.238
.034
-.345
-.507
1.000
-.189
55301045.5
-1.317
Correlatio
5%
ns
INDS./INSTIS. CEO SHARES
SHARES
VALUE CEO TURNOVER
OUTSTANDIN G Covarian
5%
1402451
-
-
-
ces
INDS./INSTIS.
97.652
242841.6
1229595.7
18178597.01
96
18
1 3126052.340
CEO SHARES
-
884544.7
162088.79
VALUE
242841.6
47
4
95 -.019
.230
1977547.98
96
8
CEO
-
162088.7
3411877.3
20959547.73
TURNOVER
1229595.
94
60
6
-.015
-
-1.762
4418838.57
718 CEO AGE
-
9
-
3126052.
20959547.
1990016946.
1817859
340
736
570
-.042
-
6.117
26635892.0
7.011
24
CEO TENURE
-.189
-.019
-.015
-.042
.000
-.190
.000
5% MGMT
5530104
-
-
-
-.190
529921911.
-46.838
5.595
1977547.
4418838.5
26635892.02
988
79
4
.230
-1.762
6.117
CEO SHARES
-1.317
783 .000
-46.838
.000
OUTSTANDIN G
552 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics
a
Model
Variance Proportions CEO Condition
5%
CEO
CEO SHARES
SHARES
CEO
CEO
MGMT
Eigenvalue
Index
(Constant)
AGE
OUTSTANDING
VALUE
TENURE
TURNOVER
1
4.400
1.000
.00
.00
.01
.01
.01
.00
.01
2
1.321
1.825
.00
.00
.04
.08
.00
.18
.05
3
.869
2.250
.00
.00
.01
.07
.02
.67
.03
4
.615
2.674
.00
.00
.01
.63
.01
.01
.19
5
.302
3.819
.01
.01
.20
.12
.10
.00
.01
6
.274
4.004
.00
.00
.42
.05
.21
.06
.58
7
.199
4.701
.02
.04
.29
.01
.60
.06
.12
8
.020
14.922
.97
.94
.00
.03
.05
.02
.00
a. Dependent Variable: BONUS
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
553 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
-84840.57
437153.44
150893.14
63899.146
211
-3.689
4.480
.000
1.000
211
11770.607
67427.289
25256.932
11907.222
211
-96705.96
441724.19
150629.73
63802.293
211
204642.453 -1.428
409360.969
.000
140932.005
211
Std. 2.856 Residual Stud. -1.445 2.867 Residual Deleted 412623.063 Residual 211824.188 Stud. -1.449 2.920 Deleted Residual Mahal. .421 45.472 Distance Cook's .000 .085 Distance Centered .002 .217 Leverage Value a. Dependent Variable: BONUS
.000
.983
211
.001
1.000
211
263.408
145826.512
211
.003
1.005
211
6.967
7.846
211
.004
.010
211
.033
.037
211
554 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
555 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
556 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
557 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
558 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
559 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 3.3 NYSE SMALL SIZE COMPANIES (SALARY VS. CEO AGE, CEO SHARES OUTSTANDING CEO SHARES VALUE, CEO TENURE, 5% MANAGEMENT AND INDIVIDUAL/INSTITUTIONAL OWNERSHIP) Descriptive Statistics Mean
Std. Deviation
N
SALARY
440822.77
133200.843
232
CEO AGE
56.57
7.338
232
CEO SHARES
2720576.73
5528056.959
232
36935990.76
138083250.839
232
CEO TENURE
10.30
6.314
232
CEO
.05
.213
232
5% MGMT
1.05
.924
232
5%
3.15
2.129
232
OUTSTANDING CEO SHARES VALUE
TURNOVER
INDS./INSTIS.
Model Summary
b
Model
Change Statistics
R 1
.369
a
Adjusted
Std. Error
R
R
R
of the
Square
F
Square
Square
Estimate
Change
Change
df1
.136
.109
125739.872
.136
5.032
7
Sig. F
Durbin-
df2
Change
Watson
224
.000
.714
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: SALARY
560 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
556953861246.713
7
79564837320.959
5.032
.000
Residual
3541555425390.180
224
15810515291.920
Total
4098509286636.890
231
a
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: SALARY
561 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations
Pearson Correlatio n
Sig. (1tailed)
N
SALA RY
CEO AGE
CEO SHARE S OUTST ANDING
CEO SHARE S VALUE
CEO TENUR E
CEO TURNOVE R
=/> 5% MGM T
=/> 5% INDVS./INSTI S.
SALARY
1.000
.096
-.162
-.236
.074
-.132
.079
.159
CEO AGE
.096
1.000
.281
.188
.629
-.170
.246
-.259
CEO SHARES
-.162
.281
1.000
.695
.103
-.051
.452
-.347
CEO SHARES VALUE
-.236
.188
.695
1.000
.022
-.048
.114
-.159
CEO TENURE
.074
.629
.103
.022
1.000
-.291
.236
-.086
CEO TURNOVER
-.132
-.170
-.051
-.048
-.291
1.000
-.056
.042
5% MGMT
.079
.246
.452
.114
.236
-.056
1.000
-.248
5% INDS./INSTIS.
.159
-.259
-.347
-.159
-.086
.042
-.248
1.000
SALARY
.
.072
.007
.000
.130
.022
.114
.008
CEO AGE
.072
.
.000
.002
.000
.005
.000
.000
CEO SHARES OUTSTANDING
.007
.000
.
.000
.059
.220
.000
.000
CEO SHARES VALUE
.000
.002
.000
.
.369
.232
.041
.008
CEO TENURE
.130
.000
.059
.369
.
.000
.000
.096
CEO TURNOVER
.022
.005
.220
.232
.000
.
.196
.263
5% MGMT
.114
.000
.000
.041
.000
.196
.
.000
5% INDS./INSTIS.
.008
.000
.000
.008
.096
.263
.000
.
SALARY
232
232
232
232
232
232
232
232
CEO AGE
232
232
232
232
232
232
232
232
CEO SHARES OUTSTANDING
232
232
232
232
232
232
232
232
CEO SHARES VALUE
232
232
232
232
232
232
232
232
CEO TENURE
232
232
232
232
232
232
232
232
CEO TURNOVER
232
232
232
232
232
232
232
232
5% MGMT
232
232
232
232
232
232
232
232
5% INDS./INSTIS.
232
232
232
232
232
232
232
232
562 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Unstandardized
Standardi
Coefficients
zed
t
Sig
95.0% Confidence
.
Interval for B
Correlations
Collinearity Statistics
Coefficient s B
Std.
Beta
Error
Lower
Upper
Zer
Parti
Par
Toleran
Bound
Bound
o-
al
t
ce
.165
.15
.534
VIF
ord er (Constant) CEO AGE
202562.6
81304.5
2.49
.01
42342.97
362782.2
04
46
1
3
5
33
3860.520
1542.74
2.50
.01
820.371
6900.669
2
3
-
.55
.590
6
.213
4 CEO
-.001
.003
-.062
SHARES
.09 6
-.006
.003
OUTSTANDI
-
5 -.039
-
.16
.03
2
7
1.87 3
.349
2.86 3
NG CEO
.000
.000
-.224
SHARES VALUE
-
.01
2.44
5
.000
.000
-
1780.94
TENURE
2260.351
8
-.107
-.161
.23
9
CEO
-
.20
-
1.26
6
5769.907
1249.205
.07
-
40668.3
TURNOVER
88090.84
84
-.141
3 5% MGMT
10808.9
1
11
5%
11884.02
4269.49
INDS./INSTI
6
0
.145 .190
2
4
-
.541
.07
1.84 7
9
-
.03
-
-
-
2.16
1
168232.4
7949.280
.13
6
20912.80
2.17
2 -.084
9 CEO
.460
.15
6
-
-
07
1.93
.05
5
4
2.78
.00
3
6
-387.357 3470.523
-.143
.07
9
9
20297.52
.15
9
9
.912
.13
2 42212.95
-
6
5 .128
.12
.686
0 .183
.17
1.45 9
.828
3
1.20 7
S. a. Dependent Variable: SALARY
563 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
1.09
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics
a
Model
Variance Proportions CEO Condition
5%
CEO
CEO SHARES
SHARES
CEO
CEO
MGMT
Eigenvalue
Index
(Constant)
AGE
OUTSTANDING
VALUE
TENURE
TURNOVER
1
4.590
1.000
.00
.00
.01
.00
.01
.00
.01
2
1.427
1.793
.00
.00
.07
.13
.00
.03
.00
3
.974
2.171
.00
.00
.00
.01
.01
.81
.00
4
.499
3.032
.00
.00
.03
.23
.00
.01
.24
5
.232
4.451
.00
.00
.03
.02
.29
.07
.18
6
.158
5.385
.00
.00
.80
.60
.00
.00
.56
7
.115
6.327
.03
.02
.05
.01
.38
.07
.01
8
.005
30.926
.97
.98
.01
.00
.31
.00
.00
a. Dependent Variable: SALARY
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
564 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
532571.38
440822.77
49102.502
232
238
1.869
.000
1.000
232
238
76547.273
21425.452
9301.242
232
238
525745.06
440489.93
50086.903
232
238
312731.906
.000
123820.066
232
238
.985
232
238
1.003
232
238
128535.047
232
238
1.008
232
238
9.015
232
238
.012
232
238
.039
232
238
Std. 2.487 .000 Residual Stud. 2.617 .001 Residual Deleted 346349.781 332.842 Residual Stud. 2.652 .001 Deleted Residual Mahal. 84.614 6.970 Distance Cook's .124 .005 Distance Centered .366 .030 Leverage Value a. Dependent Variable: SALARY
565 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
566 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
567 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
568 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
569 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
570 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 3.4 NYSE SMALL SIZE COMPANIES (BONUS VS. CEO AGE, CEO SHARES OUTSTANDING CEO SHARES VALUE, CEO TENURE, 5% MANAGEMENT AND INDIVIDUAL/INSTITUTIONAL OWNERSHIP) Descriptive Statistics Mean
Std. Deviation
N
BONUS
182360.46
225585.715
232
CEO AGE
56.53
7.340
232
CEO SHARES
2711908.50
5530552.111
232
37052512.12
138077354.783
232
CEO TENURE
10.22
6.349
232
CEO
.05
.222
232
5% MGMT
1.05
.927
232
5%
3.17
2.109
232
OUTSTANDING CEO SHARES VALUE
TURNOVER
INDS./INSTIS.
Model Summary
b
Model
Change Statistics
R 1
.233
a
Adjusted
Std. Error
R
R
R
of the
Square
F
Square
Square
Estimate
Change
Change
df1
.054
.025
222775.774
.054
1.838
7
Sig. F
Durbin-
df2
Change
Watson
224
.081
1.254
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: BONUS
571 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
638433092159.863
7
91204727451.409
1.838
.081
Residual
11116906223401.700
224
49629045640.186
Total
11755339315561.600
231
a
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: BONUS
572 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations
Pearson Correlatio n
Sig. (1tailed)
N
CEO SHARE S VALUE -.134
CEO TENUR E -.086
CEO TURNOVE R .090
=/> 5% MGM T -.090
=/> 5% INDVS./INSTI S.
BONUS
BONU S 1.000
CEO AGE -.004
CEO SHARES OUTSTAN DING -.178
CEO AGE
-.004
1.000
.282
.189
.631
-.169
.248
-.260
CEO SHARES
-.178
.282
1.000
.695
.106
-.053
.453
-.352
CEO SHARES VALUE
-.134
.189
.695
1.000
.023
-.046
.114
-.163
CEO TENURE
-.086
.631
.106
.023
1.000
-.303
.250
-.081
CEO TURNOVER
.090
-.169
-.053
-.046
-.303
1.000
-.075
.036
5% MGMT
-.090
.248
.453
.114
.250
-.075
1.000
-.257
5% INDS./INSTIS.
.067
-.260
-.352
-.163
-.081
.036
-.257
1.000
BONUS
.
.474
.003
.021
.097
.087
.085
.154
CEO AGE
.474
.
.000
.002
.000
.005
.000
.000
CEO SHARES OUTSTANDING
.003
.000
.
.000
.053
.209
.000
.000
CEO SHARES VALUE
.021
.002
.000
.
.361
.243
.042
.006
CEO TENURE
.097
.000
.053
.361
.
.000
.000
.109
CEO TURNOVER
.087
.005
.209
.243
.000
.
.127
.291
5% MGMT
.085
.000
.000
.042
.000
.127
.
.000
5% INDS./INSTIS.
.154
.000
.000
.006
.109
.291
.000
.
BONUS
232
232
232
232
232
232
232
232
CEO AGE
232
232
232
232
232
232
232
232
CEO SHARES OUTSTANDING
232
232
232
232
232
232
232
232
CEO SHARES VALUE
232
232
232
232
232
232
232
232
CEO TENURE
232
232
232
232
232
232
232
232
CEO TURNOVER
232
232
232
232
232
232
232
232
5% MGMT
232
232
232
232
232
232
232
232
5% INDS./INSTIS.
232
232
232
232
232
232
232
232
.067
573 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Stan dard ized Coef Unstandardized
ficie
95.0% Confidence
Coefficients
nts
Interval for B
Collinearity Correlations
Statistics
Zero Std.
(Constant)
B
Error
-
144745.
Beta
36454.02
345
4960.167
Upper
orde
Parti
r
al
Part
ance
VIF
10359.5
-
.120
.118
.531
1.882
61
.004
.002
-
-
-.100
.349
2.868
.178
.102
-
-
-.024
.460
2.172
.134
.025
-
-
-.108
.532
1.880
.086
.110
.090
.059
.057
.905
1.105
-.001
.679
1.472
.027
.823
1.215
t
Sig.
Bound
Bound
-.252
.801
-
248782.
321690.
741
1 CEO AGE
Lower
784 2739.95
.161
1.810
.072
-439.227
9 CEO
-.007
Toler
.004
-
SHARES
-1.536
.126
-.016
.169
OUTSTANDI NG CEO
.000
.000
-
SHARES
-.376
.708
.000
.000
.036
VALUE CEO
-
3165.73
-
TENURE
5253.116
4
.148
CEO
61206.58
69421.0
.060
TURNOVER
2
66
-1.659
.098
-
985.315
11491.5 46 .882
.379
-
198008.
75595.3
496
32 5% MGMT
-188.117
19186.8
-
95
.001
-.010
.992
-
37621.7
-
-
37998.0
88
.090
.001
-
18238.5
.067
.027
11961.9
77
22 5% INDS./INSTI
3138.305
7662.73 6
S.
.029
.410
.683
67
a. Dependent Variable: BONUS
574 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model
5%
5% MGMT
CEO
INDS./I
CEO
CEO
NSTIS.
SHARES
TURNOV
CEO
OUTSTANDI
VALUE
ER
CEO AGE
TENURE
NG
1.000
-.018
-.100
.077
.199
-.109
.228
-.018
1.000
.037
-.002
-.043
.258
-.005
-.100
.037
1.000
.296
-.065
.046
-.711
CEO AGE
.077
-.002
.296
1.000
.005
-.165
-.473
CEO TENURE
.199
-.043
-.065
.005
1.000
-.615
-.093
5% MGMT
-.109
.258
.046
-.165
-.615
1.000
.064
CEO SHARES
.228
-.005
-.711
-.473
-.093
.064
1.000
-.120
11261734.8
4184155.
-
7.847
37
185
2647138.2
Correlatio
5%
ns
INDS./INSTIS. CEO SHARES
SHARES
VALUE CEO TURNOVER
OUTSTANDIN G Covarian
5%
587175
-
ces
INDS./INSTIS.
27.653
9371133.410
06 CEO SHARES
-
4819284457.
VALUE
937113
523
.396
3.410 CEO
-
-
56710251.
2579800.33
8094911.
363
0
593
-1.515
-.120
.396
.000
.887
-.028
.023
.000
112617
-
.887
368136928.
250326.4
-
-40.696
34.837
2579800.330
136
28
10015726.
TURNOVER CEO AGE
746 CEO TENURE
418415
-
5.185
8094911.593
-
56710251.36
264713
3
-.028
250326.428
7507377.
-
213
5337219.4
-1.148
25 5% MGMT
.023
8.206 CEO SHARES
7.847
-1.515
.000
-
-
10021872.
10015726.7
5337219.
356
46
425
-40.696
-1.148
.904
.904
.000
OUTSTANDIN G
575 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Collinearity Diagnostics
a
Model
Variance Proportions CEO Condition
5%
CEO
CEO SHARES
SHARES
CEO
CEO
MGMT
Eigenvalue
Index
(Constant)
AGE
OUTSTANDING
VALUE
TENURE
TURNOVER
1
4.593
1.000
.00
.00
.01
.00
.01
.00
.01
2
1.428
1.793
.00
.00
.07
.13
.00
.03
.00
3
.975
2.171
.00
.00
.00
.01
.01
.80
.00
4
.499
3.032
.00
.00
.03
.22
.00
.02
.24
5
.228
4.493
.00
.00
.03
.02
.30
.07
.17
6
.158
5.384
.00
.00
.79
.60
.00
.00
.57
7
.114
6.337
.03
.02
.06
.01
.36
.08
.01
8
.005
31.037
.97
.98
.01
.00
.32
.00
.00
a. Dependent Variable: BONUS
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
576 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
-14359.20
329128.91
182360.46
52571.662
232
-3.742
2.792
.000
1.000
232
16668.855
135600.250
38020.443
16338.389
232
-22810.39
331380.59
182452.63
53121.706
232
301536.531 -1.354
627034.688
.000
219374.418
232
Std. 2.815 Residual Stud. -1.419 2.836 Residual Deleted 636380.625 Residual 331380.594 Stud. -1.422 2.881 Deleted Residual Mahal. .298 84.589 Distance Cook's .000 .056 Distance Centered .001 .366 Leverage Value a. Dependent Variable: BONUS
.000
.985
232
.000
.999
232
-92.174
226034.295
232
.002
1.004
232
6.970
8.904
232
.004
.007
232
.030
.039
232
577 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
578 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
579 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
580 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
581 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
582 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 3.5 TSX MEDIUM SIZE COMPANIES (SALARY VS. CEO AGE, CEO SHARES OUTSTANDING CEO SHARES VALUE, CEO TENURE, 5% MANAGEMENT AND INDIVIDUAL/INSTITUTIONAL OWNERSHIP) Descriptive Statistics Mean
Std. Deviation
N
SALARY
628117.41
254842.404
240
CEO AGE
54.66
5.470
240
CEO SHARES
1240475.31
2429979.202
240
35601885.08
133074456.982
240
CEO TENURE
7.39
5.799
240
CEO
.10
.301
240
5% MGMT
.23
.471
240
5%
1.05
1.140
240
OUTSTANDING CEO SHARES VALUE
TURNOVER
INDS./INSTIS.
Model Summary
b
Model
Change Statistics
R 1
.387
a
Adjusted
Std. Error
R
R
R
of the
Square
F
Square
Square
Estimate
Change
Change
df1
.149
.124
238552.420
.149
5.822
7
Sig. F
Durbin-
df2
Change
Watson
232
.000
.637
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: SALARY
583 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
2319287922686.410
7
331326846098.059
5.822
.000
Residual
13202483684485.800
232
56907257260.715
Total
15521771607172.200
239
a
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: SALARY
584 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations
Pearson Correlatio n
Sig. (1tailed)
N
CEO SHARES OUTSTA NDING -.034
CEO SHARE S VALUE .131
CEO TENUR E .264
CEO TURNOVE R -.159
=/> 5% MGM T .045
=/> 5% INDVS./INSTI S.
SALARY
SALA RY 1.000
CEO AGE .084
CEO AGE
.084
-.174
.050
.416
-.114
.068
-.022
CEO SHARES
-.034
1.000
.450
.443
-.135
.315
-.132
CEO SHARES VALUE
.131
1.00 0 .174 .050
.450
1.000
.346
-.073
.050
-.014
CEO TENURE
.264
.416
.443
.346
1.000
-.346
.027
-.210
CEO TURNOVER
-.159
.114
-.135
-.073
-.346
1.000
-.018
.121
5% MGMT
.045
.068
.315
.050
.027
-.018
1.000
-.043
5% INDS./INSTIS.
-.062
.022
-.132
-.014
-.210
.121
-.043
1.000
SALARY
.
.098
.302
.021
.000
.007
.242
.169
CEO AGE
.098
.
.003
.222
.000
.039
.145
.365
CEO SHARES OUTSTANDING
.302
.003
.
.000
.000
.018
.000
.020
CEO SHARES VALUE
.021
.222
.000
.
.000
.130
.220
.412
CEO TENURE
.000
.000
.000
.000
.
.000
.341
.001
CEO TURNOVER
.007
.039
.018
.130
.000
.
.392
.031
5% MGMT
.242
.145
.000
.220
.341
.392
.
.252
5% INDS./INSTIS.
.169
.365
.020
.412
.001
.031
.252
.
SALARY
240
240
240
240
240
240
240
240
CEO AGE
240
240
240
240
240
240
240
240
CEO SHARES OUTSTANDING
240
240
240
240
240
240
240
240
CEO SHARES VALUE
240
240
240
240
240
240
240
240
CEO TENURE
240
240
240
240
240
240
240
240
CEO TURNOVER
240
240
240
240
240
240
240
240
5% MGMT
240
240
240
240
240
240
240
240
5% INDS./INSTIS.
240
240
240
240
240
240
240
240
-.062
585 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Stan dard ized Coef Unstandardized
ficie
95.0% Confidence
Coefficients
nts
Interval for B
Collinearity Correlations
Statistics
Zero Std.
(Constant) CEO AGE
CEO
B
Error
997676.7
184859.
75
841
-
3588.27
-
8810.448
6
.189
-.041
Beta
.009
-
SHARES
Lower
Upper
orde
Parti
r
al
Part
ance
VIF
.084
-
-.149
.618
1.618
-.266
.474
2.111
t
Sig.
Bound
Bound
5.397
.000
633458.
1361895
163
.386
-2.455
.015
-
-
15880.2
1740.67
20
6
-.059
-.022
-4.392
.000
.386
Toler
.159 -
-
.034
.277
OUTSTANDI NG CEO
.000
.000
.152
2.187
.030
.000
.001
.131
.142
.132
.755
1.325
CEO
18925.11
3941.52
.431
4.801
.000
11159.3
26690.8
.264
.301
.291
.456
2.194
TENURE
9
3
65
72
CEO
-
54931.1
-
-
50322.7
-
-
-.064
.873
1.145
TURNOVER
57904.98
90
.068
166132.
51
.159
.069
86289.59
36221.6
.159
14924.2
157654.
.045
.155
.144
.819
1.220
1
18
41
941
5%
-
13953.8
-
-
25319.9
-
-
-.009
.941
1.062
INDS./INSTI
2172.430
33
.010
29664.8
97
.062
.010
SHARES VALUE
-1.054
.293
4 5% MGMT
719
S.
2.382 -.156
.018 .876
57
a. Dependent Variable: SALARY
586 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model
Correlations
Covariances
5% INDS./INSTIS.
5% MGMT
5% INDS./INSTIS.
1.000
CEO SHARES VALUE -.076
CEO SHARES VALUE
-.076
1.000
-.069
.098
-.040
-.349
-.116
CEO TURNOVER
-.059
-.069
1.000
-.258
-.049
.483
-.564
CEO AGE
.032
.098
-.258
1.000
.025
-.415
.237
CEO TENURE
-.046
-.040
-.049
.025
1.000
-.033
.285
5% MGMT
.025
-.349
.483
-.415
-.033
1.000
-.509
CEO SHARES OUTSTANDING
.164
-.116
-.564
.237
.285
-.509
1.000
5% INDS./INSTIS.
194709454.613
-.142
-2978060.058
16208163.903
-35581195.279
3.250
9043129.400
CEO SHARES VALUE
-.142
.000
-.033
.475
-.292
.000
-.061
CEO TURNOVER
-2978060.058
-.033
12875725.296
-33590609.519
-9723383.573
15.988
-7977369.661
CEO AGE
16208163.903
.475
1312005583.187
48998343.249
-35581195.279
-.292
48998343.249
3017435665.431
138.829 -16.525
33875217.536
CEO TENURE
33590609.519 -9723383.573
5% MGMT
3.250
.000
15.988
-138.829
-16.525
.000
-18.506
CEO SHARES OUTSTANDING
9043129.400
-.061
-7977369.661
33875217.536
61802466.454
-18.506
15535601.491
Collinearity Diagnostics
CEO TURNOVER -.059
CEO AGE .032
CEO TENURE -.046
.025
CEO SHARES OUTSTANDING .164
a
587 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
61802466.454
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model
Variance Proportions CEO Condition
5%
CEO
CEO SHARES
SHARES
CEO
CEO
MGMT
Eigenvalue
Index
(Constant)
AGE
OUTSTANDING
VALUE
TENURE
TURNOVER
1
4.040
1.000
.00
.00
.01
.01
.01
.00
.01
2
1.324
1.747
.00
.00
.06
.14
.00
.17
.00
3
.822
2.218
.00
.00
.02
.25
.01
.53
.00
4
.803
2.243
.00
.00
.02
.10
.01
.02
.58
5
.499
2.845
.00
.00
.03
.18
.05
.12
.12
6
.363
3.334
.00
.00
.54
.30
.01
.00
.15
7
.146
5.269
.01
.00
.09
.02
.65
.15
.07
8
.003
35.247
.99
.99
.23
.01
.27
.00
.06
a. Dependent Variable: SALARY
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
588 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
410798.53
1293249.63
628117.41
98509.561
240
-2.206
6.752
.000
1.000
240
18948.982
227410.391
39052.416
19322.864
240
412727.09
1502527.50
629185.81
105782.669
240
517867.500 -2.171
703731.750
.000
235033.014
240
Std. 2.950 Residual Stud. -2.200 2.959 Residual Deleted 708200.250 Residual 532028.438 Stud. -2.219 3.010 Deleted Residual Mahal. .512 216.200 Distance Cook's .000 .106 Distance Centered .002 .905 Leverage Value a. Dependent Variable: SALARY
.000
.985
240
-.001
.998
240
-1068.400
241715.607
240
-.001
1.003
240
6.971
14.858
240
.004
.009
240
.029
.062
240
589 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
590 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
591 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
592 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
593 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
594 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 3.6 TSX MEDIUM SIZE COMPANIES (BONUS VS. CEO AGE, CEO SHARES OUTSTANDING CEO SHARES VALUE, CEO TENURE, 5% MANAGEMENT AND INDIVIDUAL/INSTITUTIONAL OWNERSHIP) Descriptive Statistics Mean
Std. Deviation
N
BONUS
676640.55
596404.974
227
CEO AGE
54.60
5.539
227
CEO SHARES
1259448.86
2493417.557
227
36936318.78
136711743.223
227
CEO TENURE
7.49
5.903
227
CEO
.10
.302
227
5% MGMT
.25
.481
227
5%
1.05
1.170
227
OUTSTANDING CEO SHARES VALUE
TURNOVER
INDS./INSTIS.
Model Summary
b
Model
Change Statistics
R 1
.285
a
Adjusted
Std. Error
R
R
R
of the
Square
F
Square
Square
Estimate
Change
Change
df1
.081
.052
580757.988
.081
2.763
7
Sig. F
Durbin-
df2
Change
Watson
219
.009
1.310
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: BONUS
595 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
6523664801350.480
7
931952114478.641
2.763
.009
Residual
73864284984923.800
219
337279840113.807
Total
80387949786274.300
226
a
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: BONUS
596 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations
Pearson Correlatio n
Sig. (1tailed)
N
=/> 5% INDVS./INSTI S.
CEO SHARES OUTSTAN DING .155
CEO SHARE S VALUE .106
CEO TENUR E .138
CEO TURNOVE R -.088
=/> 5% MGM T .154
-.180
.052
.439
-.134
.076
-.023
1.000
.449
.449
-.139
.314
-.135
.449
1.000
.348
-.075
.045
-.016
BONUS
BONU S 1.000
CEO AGE
-.040
CEO SHARES
.155
CEO SHARES VALUE
.106
CEO AGE .040 1.00 0 .180 .052
CEO TENURE
.138
.439
.449
.348
1.000
-.360
.018
-.212
CEO TURNOVER
-.088
.134
-.139
-.075
-.360
1.000
-.021
.122
5% MGMT
.154
.076
.314
.045
.018
-.021
1.000
-.047
5% INDS./INSTIS.
-.180
.023
-.135
-.016
-.212
.122
-.047
1.000
BONUS
.
.273
.010
.055
.019
.093
.010
.003
CEO AGE
.273
.
.003
.219
.000
.022
.128
.367
CEO SHARES OUTSTANDING
.010
.003
.
.000
.000
.018
.000
.021
CEO SHARES VALUE
.055
.219
.000
.
.000
.129
.248
.406
CEO TENURE
.019
.000
.000
.000
.
.000
.395
.001
CEO TURNOVER
.093
.022
.018
.129
.000
.
.379
.033
5% MGMT
.010
.128
.000
.248
.395
.379
.
.241
5% INDS./INSTIS.
.003
.367
.021
.406
.001
.033
.241
.
BONUS
227
227
227
227
227
227
227
227
CEO AGE
227
227
227
227
227
227
227
227
CEO SHARES OUTSTANDING
227
227
227
227
227
227
227
227
CEO SHARES VALUE
227
227
227
227
227
227
227
227
CEO TENURE
227
227
227
227
227
227
227
227
CEO TURNOVER
227
227
227
227
227
227
227
227
5% MGMT
227
227
227
227
227
227
227
227
5% INDS./INSTIS.
227
227
227
227
227
227
227
227
-.180
597 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Stan dard ized Coef Unstandardized
ficie
95.0% Confidence
Coefficients
nts
Interval for B
Collinearity Correlations
Statistics
Zero Std.
(Constant) CEO AGE
B
Error
1406222.
471428.
Beta
602
820
-
9237.26
-
14776.54
0
.137
-.011
Upper
orde
Parti
r
al
Part
ance
VIF
-.104
.570
1.754
-.029
.446
2.244
t
Sig.
Bound
Bound
2.983
.003
477104.
2335340
583
.622
-1.600
.111
-
3428.76
-
-
32981.8
4
.040
.107
.035
.155
-
0 CEO
Lower
Toler
43 .023
-
SHARES
-.453
.651
-.056
.044
.031
OUTSTANDI NG CEO
.000
.000
.069
.925
.356
.000
.001
.106
.062
.060
.755
1.325
CEO
15063.02
10130.0
.149
1.487
.138
-
35027.9
.138
.100
.096
.417
2.396
TENURE
9
54
4901.84
00
CEO
-
137523.
-
-.030
.863
1.159
TURNOVER
63893.25
462
.032
SHARES VALUE
1 -.465
.643
8 5% MGMT
-
207145.
-
-
334932.
595
.088
.031
27902.6
382461.
.154
.152
.148
.799
1.252
66
722
-
-
-
-
-.140
.939
1.065
140944.
6637.71
.180
.145
957
9
111
205182.1
89950.5
.165
2.281
.024
-2.166
.031
94
52
5%
-
34073.3
-
INDS./INSTI
73791.33
37
.145
S.
8
a. Dependent Variable: BONUS
598 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model
Correlations
Covariances
5% INDS./INSTIS.
5% MGMT
5% INDS./INSTIS.
1.000
CEO SHARES VALUE -.074
CEO SHARES VALUE
-.074
1.000
-.074
.103
-.040
-.344
-.103
CEO TURNOVER
-.070
-.074
1.000
-.294
-.050
.522
-.602
CEO AGE
.042
.103
-.294
1.000
.035
-.438
.276
CEO TENURE
-.044
-.040
-.050
.035
1.000
-.042
.291
5% MGMT
.015
-.344
.522
-.438
-.042
1.000
-.544
CEO SHARES OUTSTANDING
.169
-.103
-.602
.276
.291
-.544
1.000
5% INDS./INSTIS.
1160992295.253
-.822
-22040874.140
128093528.003
-204173905.901
11.653
58315674.11
CEO SHARES VALUE
-.822
.000
-.223
3.013
-1.811
.000
-.340
CEO TURNOVER
-22040874.140
-.223
85326971.006
-244686054.117
-63593021.493
111.843
-56294549.1
CEO AGE
128093528.003
3.013
8091101785.242
429172268.078
-204173905.901
-1.811
429172268.078
18912702600.722
913.730 133.774
251485270.6
CEO TENURE
244686054.117 -63593021.493
5% MGMT
11.653
.000
111.843
-913.730
-133.774
.001
-128.010
CEO SHARES OUTSTANDING
58315674.113
-.340
-56294549.174
251485270.681
406035421.979
128.010
102617987.8
Collinearity Diagnostics
CEO TURNOVER -.070
CEO AGE .042
CEO TENURE -.044
.015
CEO SHARE OUTSTAND .169
a
599 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
406035421.9
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model
Variance Proportions CEO Condition
5%
CEO
CEO SHARES
SHARES
CEO
CEO
MGMT
Eigenvalue
Index
(Constant)
AGE
OUTSTANDING
VALUE
TENURE
TURNOVER
1
4.039
1.000
.00
.00
.01
.01
.01
.00
.01
2
1.331
1.742
.00
.00
.06
.13
.00
.17
.00
3
.821
2.218
.00
.00
.01
.29
.01
.49
.02
4
.798
2.250
.00
.00
.02
.07
.01
.05
.54
5
.502
2.837
.00
.00
.02
.16
.04
.12
.12
6
.366
3.323
.00
.00
.50
.31
.00
.00
.15
7
.141
5.345
.01
.00
.10
.02
.61
.16
.08
8
.003
36.094
.99
.99
.27
.01
.31
.00
.08
a. Dependent Variable: BONUS
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
600 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
12928.30
1198834.13
676640.55
169899.304
227
-3.907
3.074
.000
1.000
227
47637.340
553903.813
98132.540
47607.809
227
-206903.34
1287805.88
671553.51
176693.680
227
948406.563 -1.633
1732703.000
.000
571693.204
227
Std. 2.984 Residual Stud. -1.662 2.997 Residual Deleted 1748929.500 Residual 982586.938 Stud. -1.669 3.054 Deleted Residual Mahal. .525 204.587 Distance Cook's .000 .409 Distance Centered .002 .905 Leverage Value a. Dependent Variable: BONUS
.000
.984
227
.002
1.000
227
5087.033
593984.679
227
.004
1.005
227
6.969
14.433
227
.006
.028
227
.031
.064
227
601 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
602 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
603 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
604 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
605 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
606 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 3.7 NYSE MEDIUM SIZE COMPANIES (SALARY VS. CEO AGE, CEO SHARES OUTSTANDING CEO SHARES VALUE, CEO TENURE, 5% MANAGEMENT AND INDIVIDUAL/INSTITUTIONAL OWNERSHIP) Descriptive Statistics Mean
Std. Deviation
N
SALARY
692534.87
194673.057
233
CEO AGE
55.86
6.889
233
CEO SHARES
3402281.30
6046948.584
233
82991594.47
236050797.048
233
CEO TENURE
7.40
5.606
233
CEO
.10
.305
233
5% MGMT
.85
.998
233
5%
3.56
1.909
233
OUTSTANDING CEO SHARES VALUE
TURNOVER
INDS./INSTIS.
Model Summary
b
Model
Change Statistics
R 1
.488
a
Adjusted
Std. Error
R
R
R
of the
Square
F
Square
Square
Estimate
Change
Change
df1
.238
.215
172530.557
.238
10.053
7
Sig. F
Durbin-
df2
Change
Watson
225
.000
.930
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: SALARY
607 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
2094714519724.280
7
299244931389.183
10.053
.000
Residual
6697528480379.850
225
29766793246.133
Total
8792243000104.130
232
a
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: SALARY
608 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations
Pearson Correlatio n
Sig. (1tailed)
N
CEO SHARE S VALUE -.041
CEO TENUR E .232
CEO TURNOVE R -.225
=/> 5% MGM T -.238
=/> 5% INDVS./INSTI S.
SALARY
SALAR Y 1.000
CEO AGE .367
CEO SHARES OUTSTANDI NG -.111
CEO AGE
.367
1.000
.049
.122
.395
-.038
-.093
-.211
CEO SHARES
-.111
.049
1.000
.575
.120
-.066
.572
-.236
CEO SHARES VALUE
-.041
.122
.575
1.000
.141
-.094
.421
-.180
CEO TENURE
.232
.395
.120
.141
1.000
-.342
.181
-.199
CEO TURNOVER
-.225
-.038
-.066
-.094
-.342
1.000
-.050
.100
5% MGMT
-.238
-.093
.572
.421
.181
-.050
1.000
.039
5% INDS./INSTIS.
-.030
-.211
-.236
-.180
-.199
.100
.039
1.000
SALARY
.
.000
.046
.269
.000
.000
.000
.323
CEO AGE
.000
.
.228
.032
.000
.281
.079
.001
CEO SHARES OUTSTANDIN G CEO SHARES VALUE
.046
.228
.
.000
.034
.158
.000
.000
.269
.032
.000
.
.016
.076
.000
.003
CEO TENURE
.000
.000
.034
.016
.
.000
.003
.001
CEO TURNOVER
.000
.281
.158
.076
.000
.
.226
.064
5% MGMT
.000
.079
.000
.000
.003
.226
.
.278
5% INDS./INSTIS.
.323
.001
.000
.003
.001
.064
.278
.
SALARY
233
233
233
233
233
233
233
233
CEO AGE
233
233
233
233
233
233
233
233
CEO SHARES OUTSTANDIN G CEO SHARES VALUE
233
233
233
233
233
233
233
233
233
233
233
233
233
233
233
233
CEO TENURE
233
233
233
233
233
233
233
233
CEO TURNOVER
233
233
233
233
233
233
233
233
5% MGMT
233
233
233
233
233
233
233
233
5% INDS./INSTIS.
233
233
233
233
233
233
233
233
-.030
609 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Stan dard ized Coef Unstandardized
ficie
95.0% Confidence
Coefficients
nts
Interval for B
Collinearity Correlations
Statistics
Zero Std.
(Constant)
B
Error
190350.3
106095.
Beta
90
232
Lower
Upper
orde
Parti
r
al
Part
ance
VIF
.367
.302
.276
.770
1.298
-
.007
.006
.500
2.000
.002
.002
.639
1.565
.232
.095
.083
.681
1.468
-.184
.863
1.158
-.187
.579
1.727
.081
.845
1.184
t
Sig.
Bound
Bound
1.794
.074
-
399417.
18716.9
770
Toler
90 CEO AGE
8900.564
1873.18
.315
4.752
.000
1 CEO
.000
.003
.009
.105
.916
5209.34
12591.7
1
87
-.005
.005
SHARES
.111
OUTSTANDI NG CEO
.000
.000
.003
.035
.972
.000
.000
SHARES
.041
VALUE CEO
3490.717
TENURE
2448.23
.101
1.426
.155
6
-
8315.12
1333.68
2
8 CEO
-
40016.5
-
TURNOVER
126812.3
29
.198
-3.169
.002
85 5% MGMT
-
14918.4
-
47949.25
10
.246
-3.214
.002
1 5% INDS./INSTI
9000.737
6455.88 2
S.
.088
1.394
.165
-
-
-
-
205667.
47957.2
.225
.207
492
78
-
-
-
-
77346.9
18551.5
.238
.210
24
78
-
21722.4
-
.093
3720.98
62
.030
8
a. Dependent Variable: SALARY
610 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model
Correlations
Covariances
5% INDS./INSTIS.
5% MGMT
5% INDS./INSTIS.
1.000
CEO SHARES VALUE -.228
CEO SHARES VALUE
-.228
1.000
-.061
.212
-.163
-.244
-.477
CEO TURNOVER
-.031
-.061
1.000
-.132
.060
.349
.016
CEO AGE
.096
.212
-.132
1.000
-.118
-.414
-.038
CEO TENURE
.062
-.163
.060
-.118
1.000
.016
-.405
5% MGMT
.134
-.244
.349
-.414
.016
1.000
.077
CEO SHARES OUTSTANDING
.252
-.477
.016
-.038
-.405
.077
1.000
5% INDS./INSTIS.
41678415.986
-21971204.124
-7956378.186
1163180.624
.024
2120862.757
4.318
CEO SHARES VALUE
21971204.124
222558960.455
-36287788.394
5921677.921
-.146
-8902357.491
-18.843
CEO TURNOVER
-7956378.186
-36287788.394
1601322579.055
9917808.668
.143
34183693.227
1.665
CEO AGE
1163180.624
5921677.921
-9917808.668
3508808.383
-.013
-1897873.586
-.190
CEO TENURE
.024
-.146
.143
-.013
.000
.002
.000
5% MGMT
2120862.757
-8902357.491
34183693.227
.002
5993861.104
.496
CEO SHARES OUTSTANDING
4.318
-18.843
1.665
1897873.586 -.190
.000
.496
.000
Collinearity Diagnostics
CEO TURNOVER -.031
CEO AGE .096
CEO TENURE .062
.134
CEO SHARES OUTSTANDIN .252
a
611 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model
Variance Proportions CEO Condition
5%
CEO
CEO SHARES
SHARES
CEO
CEO
MGMT
Eigenvalue
Index
(Constant)
AGE
OUTSTANDING
VALUE
TENURE
TURNOVER
1
4.696
1.000
.00
.00
.01
.01
.01
.00
.01
2
1.331
1.878
.00
.00
.07
.15
.00
.10
.01
3
.902
2.282
.00
.00
.02
.03
.04
.61
.00
4
.407
3.396
.00
.00
.14
.66
.01
.01
.27
5
.304
3.931
.00
.00
.14
.10
.30
.13
.11
6
.254
4.299
.00
.00
.49
.04
.17
.09
.43
7
.100
6.862
.02
.02
.15
.00
.37
.05
.12
8
.006
28.369
.97
.97
.00
.01
.11
.01
.04
a. Dependent Variable: SALARY
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
612 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
426610.72
910981.00
692534.87
95020.745
233
-2.799
2.299
.000
1.000
233
15057.089
84865.492
29778.503
11655.884
233
428883.16
913210.19
692660.40
94970.533
233
408854.500 -2.370
512957.094
.000
169907.790
233
Std. 2.973 Residual Stud. -2.395 3.027 Residual Deleted 531605.750 Residual 417628.219 Stud. -2.421 3.083 Deleted Residual Mahal. .771 55.137 Distance Cook's .000 .043 Distance Centered .003 .238 Leverage Value a. Dependent Variable: SALARY
.000
.985
233
.000
1.002
233
-125.526
175787.292
233
.000
1.006
233
6.970
7.312
233
.004
.007
233
.030
.032
233
613 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
614 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
615 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
616 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
617 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
618 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 3.8 NYSE MEDIUM SIZE COMPANIES (BONUS VS. CEO AGE, CEO SHARES OUTSTANDING CEO SHARES VALUE, CEO TENURE, 5% MANAGEMENT AND INDIVIDUAL/INSTITUTIONAL OWNERSHIP) Descriptive Statistics Mean
Std. Deviation
N
BONUS
307643.06
394825.410
235
CEO AGE
55.78
6.867
235
CEO SHARES
3392239.86
6026116.987
235
82807129.31
235054411.810
235
CEO TENURE
7.44
5.553
235
CEO
.09
.292
235
5% MGMT
.84
.995
235
5%
3.55
1.874
235
OUTSTANDING CEO SHARES VALUE
TURNOVER
INDS./INSTIS.
Model Summary
b
Model
Change Statistics
R 1
.209
a
Adjusted
Std. Error
R
R
R
of the
Square
F
Square
Square
Estimate
Change
Change
df1
.044
.014
392007.402
.044
1.482
7
Sig. F
Durbin-
df2
Change
Watson
227
.174
1.212
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: BONUS
619 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
1594537132935.600
7
227791018990.800
1.482
.174
Residual
34883045272226.400
227
153669802961.350
Total
36477582405162.000
234
a
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: BONUS
620 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations =/> 5% INDVS./INSTIS.
CEO
Pearson Correlation
CEO
CEO SHARES
SHARES
CEO
CEO
=/> 5%
BONUS
AGE
OUTSTANDING
VALUE
TENURE
TURNOVER
MGMT
BONUS
1.000
-.102
-.155
-.137
-.064
.020
-.047
-.001
CEO AGE
-.102
1.000
.051
.123
.397
-.032
-.087
-.221
CEO SHARES
-.155
.051
1.000
.576
.117
-.052
.575
-.238
CEO SHARES
-.137
.123
.576
1.000
.140
-.087
.423
-.182
CEO TENURE
-.064
.397
.117
.140
1.000
-.336
.188
-.205
CEO TURNOVER
.020
-.032
-.052
-.087
-.336
1.000
-.036
.093
5% MGMT
-.047
-.087
.575
.423
.188
-.036
1.000
.041
5%
-.001
-.221
-.238
-.182
-.205
.093
.041
1.000
BONUS
.
.060
.009
.018
.164
.377
.238
.495
CEO AGE
.060
.
.216
.029
.000
.310
.092
.000
CEO SHARES
.009
.216
.
.000
.036
.215
.000
.000
.018
.029
.000
.
.016
.091
.000
.003
CEO TENURE
.164
.000
.036
.016
.
.000
.002
.001
CEO TURNOVER
.377
.310
.215
.091
.000
.
.292
.077
5% MGMT
.238
.092
.000
.000
.002
.292
.
.266
5%
.495
.000
.000
.003
.001
.077
.266
.
BONUS
235
235
235
235
235
235
235
235
CEO AGE
235
235
235
235
235
235
235
235
CEO SHARES
235
235
235
235
235
235
235
235
235
235
235
235
235
235
235
235
CEO TENURE
235
235
235
235
235
235
235
235
CEO TURNOVER
235
235
235
235
235
235
235
235
5% MGMT
235
235
235
235
235
235
235
235
5%
235
235
235
235
235
235
235
235
VALUE
INDS./INSTIS. Sig. (1tailed)
OUTSTANDING CEO SHARES VALUE
INDS./INSTIS. N
OUTSTANDING CEO SHARES VALUE
INDS./INSTIS.
621 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Stan dard ized Coef Unstandardized
ficie
95.0% Confidence
Coefficients
nts
Interval for B
Collinearity Correlations
Statistics
Zero Std.
(Constant) CEO AGE
B
Error
668074.0
241139.
Beta
17
318
-
4260.06
-
4647.905
7
.081
Lower
Upper
orde
Parti
r
al
Part
ance
VIF
-.071
.767
1.303
-.123
.496
2.014
-.060
.638
1.567
-.028
.677
1.478
t
Sig.
Bound
Bound
2.770
.006
192916.
1143231
343
.690
-1.091
.276
-
3746.42
-
-
13042.2
7
.102
.072
.000
-
-
.155
.125
-
-
.137
.061
Toler
36 CEO
-.011
.006
-
SHARES
-1.894
.060
-.023
.174
OUTSTANDI NG CEO
.000
.000
-
SHARES
-.922
.358
.000
.000
.075
VALUE CEO
-
5610.66
-
TENURE
2449.092
9
.034
CEO
2416.251
94356.8
.002
-.437
.663
-
8606.56
-
-
13504.7
0
.064
.029
-
188343.
.020
.002
.002
.866
1.155
183511.
616 .068
.067
.570
1.753
-.078
.837
1.195
44 TURNOVER
.026
.980
85
115 5% MGMT
35055.98
34086.8
6
69
.088
1.028
.305
-
102223.
-
32111.1
122
.047
-
11592.4
-
-
47303.0
47
.001
.079
50 5%
-
14944.5
-
INDS./INSTI
17855.32
45
.085
S.
3
-1.195
.233
93
a. Dependent Variable: BONUS
622 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model
5% INDS./INSTIS.
Correlations
Covariances
5% INDS./INSTIS.
1.000
CEO SHARES VALUE -.237
CEO SHARES VALUE
-.237
1.000
-.074
.211
-.165
-.259
-.482
CEO TURNOVER
-.023
-.074
1.000
-.139
.065
.349
.013
CEO AGE
.101
.211
-.139
1.000
-.120
-.416
-.039
CEO TENURE
.063
-.165
.065
-.120
1.000
.021
-.402
5% MGMT
.144
-.259
.349
-.416
.021
1.000
.085
CEO SHARES OUTSTANDING
.259
-.482
.013
-.039
-.402
.085
1.000
5% INDS./INSTIS.
223339418.229
-120518792.844
-32166287.521
6425545.791
.129
12061039.080
23.337
CEO SHARES VALUE
120518792.844
1161914621.293
-239336030.299
30680533.676
-.770
-49549167.888
-99.103
CEO TURNOVER
-32166287.521
-239336030.299
8903221806.148
55800174.759
.832
184840459.516
7.312
CEO AGE
6425545.791
30680533.676
-55800174.759
18148167.955
-.070
-9936535.063
-1.005
CEO TENURE
.129
-.770
.832
-.070
.000
.016
.000
5% MGMT
12061039.080
-49549167.888
184840459.516
-9936535.063
.016
31479603.305
2.892
CEO SHARES OUTSTANDING
23.337
-99.103
7.312
-1.005
.000
2.892
.000
Collinearity Diagnostics Model
5% MGMT
Eigenvalue
CEO TURNOVER -.023
CEO AGE .101
CEO TENURE .063
.144
CEO SH OUTSTA .259
a
Variance Proportions
623 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
CEO
Condition
5%
CEO
CEO SHARES
SHARES
CEO
CEO
(Constant)
AGE
OUTSTANDING
VALUE
TENURE
TURNOVER
Index
MGMT
1
4.694
1.000
.00
.00
.01
.01
.01
.00
.01
2
1.322
1.884
.00
.00
.07
.15
.00
.09
.01
3
.917
2.263
.00
.00
.02
.03
.03
.63
.00
4
.407
3.394
.00
.00
.13
.67
.01
.01
.27
5
.301
3.946
.00
.00
.13
.09
.30
.12
.12
6
.256
4.279
.00
.00
.50
.04
.17
.08
.41
7
.096
6.999
.02
.02
.15
.00
.38
.05
.13
8
.006
28.477
.97
.97
.00
.01
.11
.01
.04
a. Dependent Variable: BONUS
Residuals Statistics
Predicted Value
a
Minimum -7160.30
Maximum 458459.00
Mean 307643.06
Std. Deviation 82548.539
N 235
624 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
-3.814
1.827
.000
1.000
235
34054.941
192825.281
67176.462
26864.594
235
-9028.81
452770.66
307476.90
82829.390
235
433766.375 -1.107
1095455.000
.000
386099.525
235
Std. 2.794 Residual Stud. -1.126 2.884 Residual Deleted 1167003.875 Residual 449115.063 Stud. -1.127 2.932 Deleted Residual Mahal. .770 55.622 Distance Cook's .000 .068 Distance Centered .003 .238 Leverage Value a. Dependent Variable: BONUS
.000
.985
235
.000
1.000
235
166.160
397932.341
235
.003
1.005
235
6.970
7.444
235
.004
.008
235
.030
.032
235
625 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
626 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
627 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
628 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
629 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
630 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 3.9 TSX LARGE SIZE COMPANIES (SALARY VS. CEO AGE, CEO SHARES OUTSTANDING CEO SHARES VALUE, CEO TENURE, 5% MANAGEMENT AND INDIVIDUAL/INSTITUTIONAL OWNERSHIP) Descriptive Statistics Mean
Std. Deviation
N
SALARY
945400.53
418877.249
233
CEO AGE
54.77
4.488
233
CEO SHARES
3380432.27
15876508.031
233
130588093.64
708713010.760
233
CEO TENURE
8.03
6.776
233
CEO
.06
.246
233
5% MGMT
.33
.688
233
5%
.95
1.138
233
OUTSTANDING CEO SHARES VALUE
TURNOVER
INDS./INSTIS.
Model Summary
b
Model
Change Statistics
R 1
.390
a
Adjusted
Std. Error
R
R
R
of the
Square
F
Square
Square
Estimate
Change
Change
df1
.152
.126
391649.933
.152
5.768
7
Sig. F
Durbin-
df2
Change
Watson
225
.000
.631
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: SALARY
631 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
6193615013767.100
7
884802144823.872
5.768
.000
Residual
34512675795729.000
225
153389670203.240
Total
40706290809496.100
232
a
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: SALARY
632 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations
Pearson Correlatio n
Sig. (1tailed)
N
CEO SHARE S VALUE .347
CEO TENUR E .210
CEO TURNOVE R -.105
=/> 5% MGM T .001
=/> 5% INDVS./INSTI S.
SALARY
SALAR Y 1.000
CEO AGE .080
CEO SHARES OUTSTANDI NG .171
CEO AGE
.080
1.000
.039
-.061
.374
-.123
-.060
.117
CEO SHARES
.171
.039
1.000
.545
.260
-.055
.480
.017
CEO SHARES VALUE
.347
-.061
.545
1.000
.331
-.048
.288
.013
CEO TENURE
.210
.374
.260
.331
1.000
-.273
.169
.008
CEO TURNOVER
-.105
-.123
-.055
-.048
-.273
1.000
-.026
.011
5% MGMT
.001
-.060
.480
.288
.169
-.026
1.000
-.156
5% INDS./INSTIS.
-.018
.117
.017
.013
.008
.011
-.156
1.000
SALARY
.
.111
.004
.000
.001
.056
.495
.393
CEO AGE
.111
.
.276
.178
.000
.030
.179
.037
CEO SHARES OUTSTANDIN G CEO SHARES VALUE
.004
.276
.
.000
.000
.201
.000
.400
.000
.178
.000
.
.000
.235
.000
.424
CEO TENURE
.001
.000
.000
.000
.
.000
.005
.452
CEO TURNOVER
.056
.030
.201
.235
.000
.
.346
.434
5% MGMT
.495
.179
.000
.000
.005
.346
.
.009
5% INDS./INSTIS.
.393
.037
.400
.424
.452
.434
.009
.
SALARY
233
233
233
233
233
233
233
233
CEO AGE
233
233
233
233
233
233
233
233
CEO SHARES OUTSTANDIN G CEO SHARES VALUE
233
233
233
233
233
233
233
233
233
233
233
233
233
233
233
233
CEO TENURE
233
233
233
233
233
233
233
233
CEO TURNOVER
233
233
233
233
233
233
233
233
5% MGMT
233
233
233
233
233
233
233
233
5% INDS./INSTIS.
233
233
233
233
233
233
233
233
-.018
633 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Stan dard ized Coef Unstandardized
ficie
95.0% Confidence
Coefficients
nts
Interval for B
Collinearity Correlations
Statistics
Zero Std.
(Constant)
B
Error
597239.1
339511.
Beta
11
691
Lower
Upper
orde
Parti
r
al
Part
ance
VIF
.080
.063
.059
.799
1.251
t
Sig.
Bound
Bound
1.759
.080
-
1266268
71790.1
.421
Toler
99 CEO AGE
6113.229
6408.05
.065
.954
.341
2
-
18740.7
6514.24
01
3 CEO
.000
.002
.016
.194
.846
-.004
.005
.171
.013
.012
.578
1.730
.000
.000
.353
4.579
.000
.000
.000
.347
.292
.281
.635
1.575
4304.648
4596.17
.070
.937
.350
-
13361.7
.210
.062
.057
.682
1.467
4752.41
08 -.060
.923
1.084
-.107
.733
1.363
-.049
.953
1.049
SHARES OUTSTANDI NG CEO SHARES VALUE CEO TENURE
8
2 CEO
-
108824.
-
TURNOVER
106734.6
238
.063
-.981
.328
85 5% MGMT
-
107710.
-
-
321179.
374
.105
.065
-
9609.49
.001
-
162324.
1
744
-
43625.4
-
76357.27
74
.125
-1.750
.081
1
.116
033
5%
-
23144.5
-
INDS./INSTI
18294.82
57
.050
S.
3
-.790
.430
-
27312.9
-
-
63902.6
94
.018
.053
40
a. Dependent Variable: SALARY
634 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model
Correlations
Covariances
5% INDS./INSTIS.
5% MGMT
5% INDS./INSTIS.
1.000
CEO SHARES VALUE .030
CEO SHARES VALUE
.030
1.000
-.083
.242
-.404
-.294
-.028
CEO TURNOVER
.175
-.083
1.000
-.015
.094
-.005
-.410
CEO AGE
-.018
.242
-.015
1.000
.014
-.040
.013
CEO TENURE
-.109
-.404
.094
.014
1.000
.206
-.082
5% MGMT
-.030
-.294
-.005
-.040
.206
1.000
-.455
CEO SHARES OUTSTANDING
-.077
-.028
-.410
.013
-.082
-.455
1.000
5% INDS./INSTIS.
535670528.206
3175284.622
177093120.919
-44272885.020
16105839.660
-.031
-3.777
CEO SHARES VALUE
3175284.622
21124852.209
-16575764.042
121159347.617
11901403.822
-.062
-.273
CEO TURNOVER
177093120.919
-16575764.042
1903181985.864
-72533356.311
26398071.753
-.010
-38.064
CEO AGE
-44272885.020
121159347.617
-72533356.311
11842714751.983
10012968.812
-.199
2.960
CEO TENURE
-16105839.660
-11901403.822
26398071.753
10012968.812
41063125.714
.060
-1.118
5% MGMT
-.031
-.062
-.010
-.199
.060
.000
.000
CEO SHARES OUTSTANDING
-3.777
-.273
-38.064
2.960
-1.118
.000
.000
Collinearity Diagnostics
CEO TURNOVER .175
CEO AGE -.018
CEO TENURE -.109
-.030
CEO SHA OUTSTAN -.077
a
635 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model
Variance Proportions CEO Condition
5%
CEO
CEO SHARES
SHARES
CEO
CEO
MGMT
Eigenvalue
Index
(Constant)
AGE
OUTSTANDING
VALUE
TENURE
TURNOVER
1
3.747
1.000
.00
.00
.01
.01
.01
.00
.02
2
1.562
1.549
.00
.00
.12
.12
.00
.03
.04
3
.956
1.980
.00
.00
.01
.00
.02
.78
.01
4
.681
2.346
.00
.00
.00
.27
.00
.01
.41
5
.493
2.758
.00
.00
.21
.20
.08
.02
.03
6
.345
3.298
.00
.00
.63
.29
.05
.01
.44
7
.214
4.180
.01
.00
.01
.07
.70
.14
.03
8
.003
36.833
.99
1.00
.01
.04
.13
.00
.01
a. Dependent Variable: SALARY
Residuals Statistics
Predicted Value
a
Minimum 644784.69
Maximum 2538491.25
Mean 945400.53
Std. Deviation 163390.993
N 233
636 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
-1.840
9.750
.000
1.000
233
30664.654
365962.156
63731.294
34786.692
233
633908.44
3037425.25
949017.69
186837.457
233
855187.438 -2.184
1091076.375
.000
385696.167
233
Std. 2.786 Residual Stud. -2.217 2.802 Residual Deleted 1103694.125 Residual 881625.938 Stud. -2.237 2.846 Deleted Residual Mahal. .427 201.569 Distance Cook's .000 .355 Distance Centered .002 .869 Leverage Value a. Dependent Variable: SALARY
.000
.985
233
-.003
1.002
233
-3617.162
401376.389
233
-.003
1.005
233
6.970
16.264
233
.006
.027
233
.030
.070
233
637 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
638 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
639 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
640 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
641 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
642 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 3.10 TSX LARGE SIZE COMPANIES (BONUS VS. CEO AGE, CEO SHARES OUTSTANDING CEO SHARES VALUE, CEO TENURE, 5% MANAGEMENT AND INDIVIDUAL/INSTITUTIONAL OWNERSHIP) Descriptive Statistics Mean
Std. Deviation
N
BONUS
1273625.78
1130320.115
228
CEO AGE
54.94
4.552
228
CEO SHARES
3317451.08
16040380.892
228
130024483.73
716484589.733
228
CEO TENURE
8.02
6.762
228
CEO
.07
.248
228
5% MGMT
.32
.690
228
5%
.96
1.147
228
OUTSTANDING CEO SHARES VALUE
TURNOVER
INDS./INSTIS.
Model Summary
b
Model
Change Statistics Adjusted R
1
.282
a
R
R
R
Std. Error of
Square
F
Square
Square
the Estimate
Change
Change
df1
.080
.050
1101479.130
.080
2.720
7
Sig. F
Durbin-
df2
Change
Watson
220
.010
1.029
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: BONUS
643 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
23104168410364.500
7
3300595487194.920
2.720
.010
Residual
266916380349335.000
220
1213256274315.160
Total
290020548759699.000
227
a
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: BONUS
644 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations
Pearson Correlatio n
Sig. (1tailed)
N
CEO SHARE S VALUE .226
CEO TENUR E -.037
CEO TURNOVE R -.027
=/> 5% MGM T .101
=/> 5% INDVS./INSTI S.
BONUS
BONU S 1.000
CEO AGE -.050
CEO SHARES OUTSTANDI NG .169
CEO AGE
-.050
1.000
.033
-.066
.359
-.082
-.042
.117
CEO SHARES
.169
.033
1.000
.545
.262
-.054
.479
.022
CEO SHARES VALUE
.226
-.066
.545
1.000
.335
-.048
.289
.015
CEO TENURE
-.037
.359
.262
.335
1.000
-.276
.177
.010
CEO TURNOVER
-.027
-.082
-.054
-.048
-.276
1.000
-.048
.025
5% MGMT
.101
-.042
.479
.289
.177
-.048
1.000
-.162
5% INDS./INSTIS.
-.080
.117
.022
.015
.010
.025
-.162
1.000
BONUS
.
.225
.005
.000
.290
.344
.064
.114
CEO AGE
.225
.
.308
.160
.000
.108
.265
.039
CEO SHARES OUTSTANDIN G CEO SHARES VALUE
.005
.308
.
.000
.000
.207
.000
.369
.000
.160
.000
.
.000
.237
.000
.411
CEO TENURE
.290
.000
.000
.000
.
.000
.004
.438
CEO TURNOVER
.344
.108
.207
.237
.000
.
.235
.356
5% MGMT
.064
.265
.000
.000
.004
.235
.
.007
5% INDS./INSTIS.
.114
.039
.369
.411
.438
.356
.007
.
BONUS
228
228
228
228
228
228
228
228
CEO AGE
228
228
228
228
228
228
228
228
CEO SHARES OUTSTANDIN G CEO SHARES VALUE
228
228
228
228
228
228
228
228
228
228
228
228
228
228
228
228
CEO TENURE
228
228
228
228
228
228
228
228
CEO TURNOVER
228
228
228
228
228
228
228
228
5% MGMT
228
228
228
228
228
228
228
228
5% INDS./INSTIS.
228
228
228
228
228
228
228
228
-.080
645 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Stan dard ized Coef Unstandardized
ficie
95.0% Confidence
Coefficients
nts
Interval for B
Correlations
Statistics
Lower
Upper
Zero-
Parti
Toler
order
al
Part
ance
VIF
-.050
.025
.024
.812
1.231
Std.
(Constant)
B
Error
1150543.
945308.
Beta
346
372
t
Sig.
Bound
Bound
1.217
.225
-
3013562
712475.
.372
Collinearity
681 CEO AGE
6563.404
17818.6
.026
.368
.713
69
-
41680.5
28553.7
36
27 CEO
.005
.006
.075
.888
.375
-.006
.017
.169
.060
.057
.579
1.726
.000
.000
.236
2.900
.004
.000
.001
.226
.192
.188
.633
1.579
CEO
-
13096.1
-
-2.042
.042
-
-926.719
-.037
-
-.132
.682
1.467
TENURE
26736.59
07
.160
-.049
.920
1.087
SHARES OUTSTANDI NG CEO SHARES VALUE 52546.4
9 CEO
-
306747.
-
TURNOVER
230903.4
635
.051
17100.53
123762.
.010
3
994
5%
-
65454.9
-
INDS./INSTI
82789.20
14
.084
S.
3
-.753
.452
87 5% MGMT
.136
79 -
373636.
835443.
468
-.027
.051
442 .138
.890
-
261013.
226812.
333
.101
.009
.009
.734
1.363
-.080
-
-.082
.948
1.055
267 -1.265
.207
-
46209.7
211788.
07
.085
114
a. Dependent Variable: BONUS
646 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model
5% INDS./INSTIS.
Correlations
Covariances
5% INDS./INSTIS.
1.000
CEO SHARES VALUE .024
CEO SHARES VALUE
.024
1.000
-.075
.262
-.399
-.297
-.033
CEO TURNOVER
.188
-.075
1.000
.003
.069
-.010
-.408
CEO AGE
-.024
.262
.003
1.000
-.027
-.050
.006
CEO TENURE
-.110
-.399
.069
-.027
1.000
.208
-.069
5% MGMT
-.029
-.297
-.010
-.050
.208
1.000
-.452
CEO SHARES OUTSTANDING
-.086
-.033
-.408
.006
-.069
-.452
1.000
5% INDS./INSTIS.
4284345738.023
20735189.408
1523479647.421
-472984823.109
128206355.199
-.241
-33.8
CEO SHARES VALUE
20735189.408
171508010.406
-121672295.042
1051698794.578
-93102762.348
-.498
-2.57
CEO TURNOVER
1523479647.421
-121672295.042
15317278632.741
102424578.404
151366582.738
-.164
-302.
CEO AGE
-472984823.109
1051698794.578
102424578.404
94094111855.365
-1.979
11.11
CEO TENURE
-128206355.199
-93102762.348
151366582.738
-145853870.523
145853870.523 317504949.234
.476
-7.33
5% MGMT
-.241
-.498
-.164
-1.979
.476
.000
.000
CEO SHARES OUTSTANDING
-33.821
-2.577
-302.034
11.115
-7.333
.000
.000
Collinearity Diagnostics Model
5% MGMT
Eigenvalue
CEO TURNOVER .188
CEO AGE -.024
CEO TENURE -.110
-.029
CEO OUT -.086
a
Variance Proportions
647 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
CEO
Condition
5%
CEO
CEO SHARES
SHARES
CEO
CEO
(Constant)
AGE
OUTSTANDING
VALUE
TENURE
TURNOVER
Index
MGMT
1
3.733
1.000
.00
.00
.01
.01
.01
.00
.02
2
1.578
1.538
.00
.00
.12
.11
.00
.04
.04
3
.949
1.984
.00
.00
.01
.01
.02
.78
.01
4
.689
2.327
.00
.00
.00
.26
.00
.00
.42
5
.492
2.755
.00
.00
.22
.21
.08
.02
.03
6
.343
3.298
.00
.00
.62
.28
.05
.01
.44
7
.213
4.182
.01
.00
.01
.08
.71
.15
.03
8
.003
36.032
.99
1.00
.01
.04
.13
.00
.01
a. Dependent Variable: BONUS
Residuals Statistics
Predicted Value
a
Minimum 493185.91
Maximum 4212698.50
Mean 1273625.78
Std. Deviation 319030.528
N 228
648 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
-2.446
9.213
.000
1.000
228
86846.797
1030285.313
181223.171
98850.468
228
504011.78
9467038.00
1312706.38
691394.924
228
2310796.000 -2.098
3191302.500
.000
1084362.986
228
Std. 2.897 Residual Stud. -2.608 3.043 Residual Deleted 3520994.000 Residual 8121271.500 Stud. -2.643 3.102 Deleted Residual Mahal. .416 197.609 Distance Cook's .000 5.945 Distance Centered .002 .871 Leverage Value a. Dependent Variable: BONUS
.000
.984
228
-.010
1.023
228
-39080.599
1270992.308
228
-.008
1.030
228
6.969
16.117
228
.036
.400
228
.031
.071
228
649 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
650 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
651 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
652 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
653 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
654 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 3.11 NYSE LARGE SIZE COMPANIES (SALARY VS. CEO AGE, CEO SHARES OUTSTANDING CEO SHARES VALUE, CEO TENURE, 5% MANAGEMENT AND INDIVIDUAL/INSTITUTIONAL OWNERSHIP) Descriptive Statistics Mean
Std. Deviation
N
SALARY
1017878.06
336670.050
235
CEO AGE
55.10
9.715
235
CEO SHARES
2434612.55
4674198.270
235
102543277.32
323526371.454
235
CEO TENURE
7.16
4.911
235
CEO
.07
.260
235
5% MGMT
.25
.571
235
5%
2.41
1.613
235
OUTSTANDING CEO SHARES VALUE
TURNOVER
INDS./INSTIS.
Model Summary
b
Model
Change Statistics
R 1
.381
a
Adjusted
Std. Error
R
R
R
of the
Square
F
Square
Square
Estimate
Change
Change
df1
.145
.119
316080.346
.145
5.497
7
Sig. F
Durbin-
df2
Change
Watson
227
.000
.778
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: SALARY
655 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
3844292919760.450
7
549184702822.921
5.497
.000
Residual
22678840178173.600
227
99906784925.875
Total
26523133097934.000
234
a
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: SALARY
656 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations
Pearson Correlatio n
Sig. (1tailed)
N
CEO SHARE S VALUE .154
CEO TENUR E .178
CEO TURNOVE R -.166
=/> 5% MGM T -.050
=/> 5% INDVS./INSTI S.
SALARY
SALAR Y 1.000
CEO AGE .136
CEO SHARES OUTSTANDI NG .033
CEO AGE
.136
1.000
.120
.169
.317
-.076
.043
.083
CEO SHARES
.033
.120
1.000
.808
.454
-.022
.448
-.024
CEO SHARES VALUE
.154
.169
.808
1.000
.504
.016
.452
-.008
CEO TENURE
.178
.317
.454
.504
1.000
-.284
.358
-.040
CEO TURNOVER
-.166
-.076
-.022
.016
-.284
1.000
-.037
-.082
5% MGMT
-.050
.043
.448
.452
.358
-.037
1.000
.008
5% INDS./INSTIS.
-.176
.083
-.024
-.008
-.040
-.082
.008
1.000
SALARY
.
.019
.310
.009
.003
.005
.223
.003
CEO AGE
.019
.
.034
.005
.000
.124
.254
.102
CEO SHARES OUTSTANDIN G CEO SHARES VALUE
.310
.034
.
.000
.000
.366
.000
.355
.009
.005
.000
.
.000
.402
.000
.449
CEO TENURE
.003
.000
.000
.000
.
.000
.000
.272
CEO TURNOVER
.005
.124
.366
.402
.000
.
.288
.106
5% MGMT
.223
.254
.000
.000
.000
.288
.
.454
5% INDS./INSTIS.
.003
.102
.355
.449
.272
.106
.454
.
SALARY
235
235
235
235
235
235
235
235
CEO AGE
235
235
235
235
235
235
235
235
CEO SHARES OUTSTANDIN G CEO SHARES VALUE
235
235
235
235
235
235
235
235
235
235
235
235
235
235
235
235
CEO TENURE
235
235
235
235
235
235
235
235
CEO TURNOVER
235
235
235
235
235
235
235
235
5% MGMT
235
235
235
235
235
235
235
235
5% INDS./INSTIS.
235
235
235
235
235
235
235
235
-.176
657 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Model
Stan dard ized Coef Unstandardized
ficie
95.0% Confidence
Coefficients
nts
Interval for B
Collinearity Correlations
Statistics
Zero Std.
(Constant) CEO AGE
B
Error
952405.9
123969.
Beta
45
396
3138.261
2265.81
.091
Lower
Upper
orde
Parti
r
al
Part
ance
VIF
.136
.092
.085
.881
1.135
.033
-
-.153
.335
2.982
t
Sig.
Bound
Bound
7.683
.000
708128.
1196683
029
.861
1.385
.167
-
7602.98
1326.46
6
8
Toler
3 CEO
-.019
.008
-
SHARES
-2.496
.013
-.034
-.004
.265
.163
OUTSTANDI NG CEO
.000
.000
.380
3.444
.001
.000
.001
.154
.223
.211
.309
3.232
4785.424
5490.68
.070
.872
.384
-
15604.6
.178
.058
.053
.587
1.703
6033.80
57 -.162
.874
1.144
-.119
.751
1.331
-.195
.976
1.025
SHARES VALUE CEO TENURE
8
9 CEO
-
85126.8
-
TURNOVER
224471.4
75
.173
-2.637
.009
25 5% MGMT
-
41780.7
-
80728.94
37
.137
-1.932
.055
7
-
-
-
-
392211.
56731.5
.166
.172
338
12
-
1598.72
-
-
163056.
2
.050
.127
-
-
-
-
66731.6
15631.0
.176
.206
28
57
615
5%
-
12966.5
-
INDS./INSTI
41181.34
98
.197
S.
2
-3.176
.002
a. Dependent Variable: SALARY
658 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model
Correlations
Covariances
5% INDS./INSTIS.
5% MGMT
5% INDS./INSTIS.
1.000
CEO SHARES VALUE -.034
CEO SHARES VALUE
-.034
1.000
-.018
.084
-.142
-.170
-.126
CEO TURNOVER
.105
-.018
1.000
-.024
.035
.331
-.150
CEO AGE
-.104
.084
-.024
1.000
.040
-.282
-.053
CEO TENURE
.029
-.142
.035
.040
1.000
-.058
-.718
5% MGMT
.100
-.170
.331
-.282
-.058
1.000
-.246
CEO SHARES OUTSTANDING
-.035
-.126
-.150
-.053
-.718
-.246
1.000
5% INDS./INSTIS.
168132653.081
-18443699.195
115778176.096
3047435.653
2.840
7110588.203
-.052
CEO SHARES VALUE
-18443699.195
1745629976.295
-62571390.222
7935402.297
-45.319
-39074081.685
-.602
CEO TURNOVER
115778176.096
-62571390.222
7246584921.896
4638477.555
22.979
154730444.900
-1.470
CEO AGE
-3047435.653
7935402.297
-4638477.555
5133929.226
.696
-3503455.547
-.014
CEO TENURE
2.840
-45.319
22.979
.696
.000
-2.450
.000
5% MGMT
7110588.203
-39074081.685
154730444.900
-2.450
30147652.647
-.155
CEO SHARES OUTSTANDING
-.052
-.602
-1.470
3503455.547 -.014
.000
-.155
.000
Collinearity Diagnostics
CEO TURNOVER .105
CEO AGE -.104
CEO TENURE .029
.100
CEO SHA OUTSTAN -.035
a
659 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Model
Variance Proportions CEO Condition
5%
CEO
CEO SHARES
SHARES
CEO
CEO
MGMT
Eigenvalue
Index
(Constant)
AGE
OUTSTANDING
VALUE
TENURE
TURNOVER
1
4.505
1.000
.00
.00
.01
.01
.01
.00
.01
2
1.430
1.775
.00
.00
.04
.06
.00
.03
.05
3
.953
2.174
.00
.00
.00
.01
.01
.77
.00
4
.544
2.877
.00
.00
.04
.06
.00
.00
.91
5
.272
4.069
.00
.00
.01
.01
.20
.01
.01
6
.172
5.118
.00
.00
.79
.55
.09
.01
.00
7
.110
6.404
.05
.04
.10
.29
.67
.17
.01
8
.014
17.806
.94
.95
.01
.01
.02
.00
.01
a. Dependent Variable: SALARY
Residuals Statistics
a
Minimum
Maximum
Mean
Std. Deviation
N
660 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
615542.19
1494998.13
1017878.06
128174.109
235
-3.139
3.722
.000
1.000
235
25039.037
173778.188
51551.390
27326.064
235
500584.34
1586503.25
1016677.89
135631.401
235
947508.625 -2.998
723386.813
.000
311316.753
235
Std. 2.289 Residual Stud. -3.035 2.368 Residual Deleted 774420.938 Residual 971190.063 Stud. -3.092 2.392 Deleted Residual Mahal. .473 69.736 Distance Cook's .000 .085 Distance Centered .002 .298 Leverage Value a. Dependent Variable: SALARY
.000
.985
235
.002
1.000
235
1200.176
320983.132
235
.001
1.004
235
6.970
10.445
235
.004
.009
235
.030
.045
235
661 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
662 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
663 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
664 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
665 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
666 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
SECTION 3.12 NYSE LARGE SIZE COMPANIES (BONUS VS. CEO AGE, CEO SHARES OUTSTANDING CEO SHARES VALUE, CEO TENURE, 5% MANAGEMENT AND INDIVIDUAL/INSTITUTIONAL OWNERSHIP) Descriptive Statistics Mean
Std. Deviation
N
BONUS
707617.42
1045248.710
223
CEO AGE
55.45
10.042
223
CEO SHARES
2043706.73
3703990.713
223
90847180.78
320136882.852
223
CEO TENURE
7.15
4.970
223
CEO
.08
.266
223
5% MGMT
.24
.573
223
5%
2.47
1.605
223
OUTSTANDING CEO SHARES VALUE
TURNOVER
INDS./INSTIS.
Model Summary
b
Model
Change Statistics Adjusted R
1
.283
a
R
R
R
Std. Error of
Square
F
Square
Square
the Estimate
Change
Change
df1
.080
.050
1018598.207
.080
2.681
7
Sig. F
Durbin-
df2
Change
Watson
215
.011
1.137
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: BONUS
667 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
ANOVA
b
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
19473364233221.900
7
2781909176174.560
2.681
.011
Residual
223071596036905.000
215
1037542307148.400
Total
242544960270127.000
222
a
a. Predictors: (Constant), =/> 5% OF INSTITUTIONAL OWNERSHIP, CEO SHARES VALUE, CEO TURNOVER, CEO AGE, CEO TENURE, =/> 5% OF MGMT OWNERSHIP, CEO SHARES OUTSTANDING b. Dependent Variable: BONUS
668 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Correlations
Pearson Correlatio n
Sig. (1tailed)
N
CEO SHARE S VALUE .060
CEO TENUR E -.019
CEO TURNOVE R -.002
=/> 5% MGM T .143
=/> 5% INDVS./INSTI S.
BONUS
BONU S 1.000
CEO AGE -.051
CEO SHARES OUTSTANDI NG -.012
CEO AGE
-.051
1.000
.179
.181
.305
-.085
.041
.057
CEO SHARES
-.012
.179
1.000
.875
.507
.001
.479
-.015
CEO SHARES VALUE
.060
.181
.875
1.000
.505
.028
.446
.001
CEO TENURE
-.019
.305
.507
.505
1.000
-.288
.349
-.056
CEO TURNOVER
-.002
-.085
.001
.028
-.288
1.000
-.033
-.095
5% MGMT
.143
.041
.479
.446
.349
-.033
1.000
-.002
5% INDS./INSTIS.
-.157
.057
-.015
.001
-.056
-.095
-.002
1.000
BONUS
.
.225
.432
.187
.391
.488
.016
.010
CEO AGE
.225
.
.004
.003
.000
.102
.274
.200
CEO SHARES OUTSTANDIN G CEO SHARES VALUE
.432
.004
.
.000
.000
.493
.000
.411
.187
.003
.000
.
.000
.341
.000
.495
CEO TENURE
.391
.000
.000
.000
.
.000
.000
.204
CEO TURNOVER
.488
.102
.493
.341
.000
.
.312
.079
5% MGMT
.016
.274
.000
.000
.000
.312
.
.488
5% INDS./INSTIS.
.010
.200
.411
.495
.204
.079
.488
.
BONUS
223
223
223
223
223
223
223
223
CEO AGE
223
223
223
223
223
223
223
223
CEO SHARES OUTSTANDIN G CEO SHARES VALUE
223
223
223
223
223
223
223
223
223
223
223
223
223
223
223
223
CEO TENURE
223
223
223
223
223
223
223
223
CEO TURNOVER
223
223
223
223
223
223
223
223
5% MGMT
223
223
223
223
223
223
223
223
5% INDS./INSTIS.
223
223
223
223
223
223
223
223
-.157
669 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficients
a
Sta nda rdiz ed Co effi cie nts
Model
Unstandardized Coefficients
B 1280465. 279
Std. Error 404618. 459
CEO AGE
2308.547
7206.11 5
CEO SHARES OUTSTANDI NG
-.094
.039
CEO SHARES VALUE
.001
.000
CEO TENURE
19971.33 8
17994.5 85
CEO TURNOVER
194227.5 55
276691. 436
5% MGMT
351089.5 40
138021. 936
5% INDS./INSTI S.
111119.3 01
43186.1 50
(Constant)
Bet a
95.0% Confidence Interval for B
Collinearity Statistics Tole ranc e VIF
Lower Bound 48293 8.375 16512. 225 -.172
Upper Bound 20779 92.183 11895. 130
Zeroorder
Par tial
-.051
.021
.892
1.12 0
-.017
-.012
.02 2 .16 1
.157
.220
4.53 5
.02 1
.000
.002
.060
.15 6
.152
.225
4.44 0
1.11 0 -.702
.26 8
15497. 053
-.019
.584
1.71 2
35114 7.623
-.002
.046
.863
1.15 9
.01 2 .01 1
62313 8.935 25996. 847
.143
.07 5 .04 8 .17 1 .17 3
.073
2.54 4 2.57 3
55439. 728 73960 2.734 79040. 145 19624 1.755
.166
.747
.168
.973
1.33 9 1.02 7
t 3.16 5 -.320
Sig. .00 2 .74 9
2.39 7
.01 7
.32 0
2.31 9
.09 5 .04 9 .19 3 .17 1
.02 2 .33 4
Correlations
.48 3
-.157
Part
a. Dependent Variable: BONUS
670 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Coefficient Correlations
a
Model
5% INDS./INSTIS.
Correlations
Covariances
5% INDS./INSTIS.
1.000
CEO SHARES VALUE -.050
CEO SHARES VALUE
-.050
1.000
-.116
-.014
-.043
-.163
-.80
CEO TURNOVER
.126
-.116
1.000
-.006
-.007
.343
-.00
CEO AGE
-.078
-.014
-.006
1.000
.094
-.249
-.02
CEO TENURE
-.020
-.043
-.007
.094
1.000
-.146
-.18
5% MGMT
.118
-.163
.343
-.249
-.146
1.000
-.10
CEO SHARES OUTSTANDING
.026
-.803
-.004
-.024
-.186
-.109
1.00
5% INDS./INSTIS.
1865043513.954
-.971
1506076648.006
24359784.930
-120747299.865
91493336.733
44.1
CEO SHARES VALUE
-.971
.000
-14.479
-.047
-2.692
-1.323
.000
CEO TURNOVER
1506076648.006
-14.479
76558150686.659
12148039.565
-264391280.083
1710206922.818
-38.
CEO AGE
-24359784.930
-.047
-12148039.565
51928087.957
93624157.250
-32313690.295
-6.8
CEO TENURE
-120747299.865
-2.692
-264391280.083
93624157.250
19050054725.571
-363816736.971
-100
5% MGMT
91493336.733
-1.323
1710206922.818
-363816736.971
323805082.053
-76.
CEO SHARES OUTSTANDING
44.190
.000
-38.817
32313690.295 -6.843
-1007.623
-76.901
.002
Collinearity Diagnostics Model
5% MGMT
Eigenvalue
CEO TURNOVER .126
CEO AGE -.078
CEO TENURE -.020
.118
CEO OUT .026
a
Variance Proportions
671 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
CEO
Condition
5%
CEO
CEO SHARES
SHARES
CEO
CEO
(Constant)
AGE
OUTSTANDING
VALUE
TENURE
TURNOVER
Index
MGMT
1
4.521
1.000
.00
.00
.00
.00
.01
.00
.01
2
1.466
1.756
.00
.00
.02
.05
.00
.02
.05
3
.958
2.173
.00
.00
.00
.00
.01
.76
.00
4
.553
2.859
.00
.00
.02
.05
.00
.01
.91
5
.270
4.090
.00
.00
.00
.02
.22
.01
.01
6
.122
6.080
.03
.02
.33
.12
.57
.12
.00
7
.096
6.875
.02
.03
.62
.75
.19
.07
.02
8
.015
17.381
.94
.94
.00
.01
.01
.01
.01
a. Dependent Variable: BONUS
Residuals Statistics
Predicted Value
a
Minimum -102914.34
Maximum 1496096.25
Mean 707617.42
Std. Deviation 296172.006
N 223
672 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual
-2.737
2.662
.000
1.000
223
82500.531
529460.938
172796.579
85998.580
223
-304814.50
1929992.38
713674.37
318260.861
223
1496096.250 -1.469
2997834.250
.000
1002410.599
223
Std. 2.943 Residual Stud. -1.668 2.972 Residual Deleted 3057678.750 Residual 1929992.375 Stud. -1.675 3.028 Deleted Residual Mahal. .461 58.986 Distance Cook's .000 .184 Distance Centered .002 .266 Leverage Value a. Dependent Variable: BONUS
.000
.984
223
-.003
1.006
223
-6056.946
1049181.771
223
.000
1.011
223
6.969
9.465
223
.006
.017
223
.031
.043
223
673 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
674 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
675 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
676 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
677 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
678 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
679 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
680 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
681 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
682 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
683 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
684 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
685 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
686 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
687 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
688 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
689 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
690 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
CEO Cash Compensation, Firm Size, Firm Performance, and CEO Power
691 Mr. Yusuf Mohammed Nulla Final Submission To The Dissertation Committee UGSM-Monarch Business School Switzerland 25-April-2013
