okiro corporate governance, capital structure, regulatory
TRANSCRIPT
CORPORATE GOVERNANCE, CAPITAL STRUCTURE, REGULATORY
COMPLIANCE AND PERFORMANCE OF FIRMS LISTED AT THE E AST
AFRICAN COMMUNITY SECURITIES EXCHANGE
KENNEDY O. OKIRO
A RESEARCH THESIS SUBMITTED IN FULFILMENT OF THE
REQUIREMENT FOR THE AWARD OF THE DEGREE OF DOCTOR O F
PHILOSOPHY (PhD) IN BUSINESS ADMINISTRATION, SCHOOL OF
BUSINESS, UNIVERSITY OF NAIROBI.
NOVEMBER 2014
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DECLARATION
This Ph D Research thesis is my original work and has not been submitted for a degree
course in any other University
Signature:_____________________________ Date:____________________
Kennedy O. Okiro
This thesis was developed with our guidance as university supervisors
Signature:_____________________________ Date:____________________
Dr. Josiah O. Aduda
Dean,
School of Business
University of Nairobi
Signature:_____________________________ Date:____________________
Professor Erasmus S. Kaijage
Department of Finance and Accounting
School of Business
University of Nairobi
Signature:_____________________________ Date:____________________
Professor Martin Ogutu
Department of Business Administration
School of Business
University of Nairobi
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DEDICATION
To God almighty for being the light of my life.
To my late father Samson Okiro who never lived long enough to see the academic
achievements of his children.
To my wonderful family, my wife Beatrice, My lovely children David, Samson, Gerry
and Anthony, and my mum Elizabeth, thank you very much guys for always being there
for me. Thanks for the encouragement, support and prayers. You are one of a kind.
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ACKNOWLEDGEMENTS
I would like to express my sincere gratitude and appreciation to the following persons for
the help they gave me and whose contribution facilitated the successful completion of my
doctoral studies:
My special thanks to my supervisors, Dr. Josiah Aduda, Prof. Erasmus Kiajage and Prof.
Martin Ogutu, for the support, advice, constructive criticism and guidance they gave me
throughout the research process. Their continuous guide and encouragement have been
invaluable.
I sincerely thank Dr Josiah Aduda, Dean School of Business and my colleagues at the
University of Nairobi, for their support. My gratitude to Handel and Joshua for their
guidance in data analysis, and Irene Mbugua for her assistance in data collection
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ABSTRACT
The purpose of the study was to establish the effect of corporate governance, capital structure, and regulatory compliance on performance of firms listed at the East African community securities exchange. Specifically the study sought to establish the effect of capital structure and regulatory compliance on the relationship between corporate governance and firm performance of listed companies in Kenya, Tanzania, Uganda, Rwanda and Burundi. The moderating, intervening and the joint effects of capital structure and regulatory compliance on the relationship between corporate governance and firm performance were tested. Based on the agency theory this study builds a comprehensive framework to answer the research question on whether good corporate governance affects firms performance by integrating capital structure and regulatory compliance into the governance model. A census survey was carried out on all the 98 listed companies between 2009 and 2013 in Nairobi Securities Exchange, Uganda Securities Exchange, Dar es Salaam Stock Exchange and Rwanda Stock Exchange. Out of the 98 firms that were targeted, 56 were analyzed constituting 57%. The study developed a Corporate Governance Index as a proxy for corporate governance and the index constitutes board structure and composition, ownership and shareholding, transparency, disclosures and auditing, board remuneration and corporate ethics. The accounting and market based measures were used as firm performance measurements and for comparison purposes the cost of capital was also considered. Hypotheses were tested using regression analysis and Pearson’s Product Moment Correlation analysis. Descriptive statistics were computed for the listed companies and the main characteristics of the study variables. The findings revealed that the influence of corporate governance on firm performance was statistically significant. There was a significant positive relationship between corporate governance and firm performance. The study also confirmed that there is a positive significant intervening effect of capital structure (leverage) and a positive significant moderating effect of regulatory compliance on the relationship between corporate governance and firm performance. The joint effect of capital structure and regulatory compliance on firm performance was greater than the individual effects of capital structure and regulatory compliance on firm performance. From a theoretical perspective, this study not only explains how corporate governance affects firm performance, but also uncovers the importance of capital structure and regulatory compliance in a corporate governance system. The study not only contributes to understanding the link between corporate governance and firm performance but at the same time confirms the findings of previous studies that have found a significant link between corporate governance and firm performance. The study brings out an increased understanding that the combinative effect of the study variables is greater than the individual effects therefore organizations can enhance their performance by implementing good corporate governance practices.
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ABBREVIATIONS AND ACRONYMS
BCCI Bank of Commerce and Credit International
BOD Board of Directors
CACG Commonwealth Association for Corporate Governance
CAR Cumulative Abnormal Returns
CCG Codes of Corporate Governance
CEO Chief Executive Officer
CFO Chief Finance Officer
CG Corporate Governance
CGI Corporate Governance Index
CMA Capital Markets Authority
CMSA Capital Markets and Security Authority
COC Cost of Capital
COD Cost of Debt
COE Cost of Equity
COEC Cost of Equity Capital
CS Capital Structure
DSE Dar es Salaam Stock Exchange
EACSE East African Community Security Exchanges
EASRA East African Securities Regulatory Authority
E-Index Entrenchment Index
ESOP Executive Share Option Plans
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EVA Economic Value Added
G-Index Governance Index
G-Score Governance Score
IMF International Monetary Fund
IRRC Investor Responsibility Research Centre
ISS Institutional Shareholder Services
NED Non-Executive Director
NSE Nairobi Securities Exchange
OECD Organization for Economic Co-operation and Development
OLS Ordinary Least Square
PSCGT Private Sector Corporate Governance Trust
RC Regulatory Compliance
ROA Return on Assets
ROCE Return on Capital Employed
ROE Return on Equity
ROTCE Rwanda over the Counter Exchange
RSA Rwanda Stock Exchange
S & P Standard and Poor
SEC Securities and Exchange Commission
SMEs Small and Medium Enterprises
USE Uganda Securities Exchange
WACC Weighted Average Cost of Capital
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TABLE OF CONTENTS
DECLARATION............................................................................................................... ii
DEDICATION.................................................................................................................. iii
ACKNOWLEDGEMENTS ............................................................................................ iv
ABSTRACT ....................................................................................................................... v
ABBREVIATIONS AND ACRONYMS ........................................................................ vi
LIST OF TABLES ......................................................................................................... xiv
LIST OF FIGURES ...................................................................................................... xvii
CHAPTER ONE: INTRODUCTION ............................................................................. 1
1.1 Background of the Study .............................................................................................. 1
1.1.1 Corporate Governance ...................................................................................... 3
1.1.2 Capital Structure ............................................................................................... 6
1.1.3 Regulatory Compliance .................................................................................... 9
1.1.4 Firm Performance ........................................................................................... 11
1.1.5 East African Community Securities Exchange ............................................... 13
1.2 Research Problem ....................................................................................................... 16
1.3 Research Objectives .................................................................................................... 20
1.4 Value of the Study ...................................................................................................... 21
CHAPTER TWO: LITERATURE REVIEW .............................................................. 23
2.1 Introduction ................................................................................................................. 23
2.2 Theoretical Foundation ............................................................................................... 23
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2.2.1 Agency Theory................................................................................................ 23
2.2.2 Stakeholder Theory ......................................................................................... 27
2.2.3 Stewardship Theory ........................................................................................ 29
2.2.4 Institutional Theory ......................................................................................... 32
2.2.5 Political Theory ............................................................................................... 33
2.2.6 The Modigliani-Miller Theorem ..................................................................... 34
2.2.7 Trade-Off Theory ............................................................................................ 35
2.2.8 Free Cash Flow Theory ................................................................................... 36
2.2.8 Summary of Theoretical Foundation .............................................................. 38
2.3 Internal Corporate Governance Mechanisms .............................................................. 38
2.3.1 Board of Directors........................................................................................... 39
2.3.2 Board size........................................................................................................ 40
2.3.3 Board Independence ........................................................................................ 41
2.3.4 CEO duality .................................................................................................... 42
2.3.5 Interlocking directorates ................................................................................. 42
2.3.6 Frequency of board meetings .......................................................................... 43
2.3.7 Board Diversity ............................................................................................... 44
2.3.8 Director and executive compensation ............................................................. 45
2.3.9 Board and managerial ownership.................................................................... 46
2.4 External Corporate Governance Mechanisms ............................................................ 46
2.4.1 Large block holders......................................................................................... 47
2.4.2 Legal system ................................................................................................... 48
2.4.3 Leverage .......................................................................................................... 48
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2.5 Corporate Governance Codes ..................................................................................... 49
2.5.1 The OECD principles for effective corporate governance ............................. 50
2.5.2 CACG principles of effective corporate governance ...................................... 52
2.5.3 Corporate governance codes in East African Countries ................................. 53
2.5.4 Models of Corporate Governance ................................................................... 54
2.6 Empirical Studies ........................................................................................................ 56
2.6.1 Corporate Governance and Firm Performance ............................................... 56
2.6.2Corporate Governance and Capital Structure .................................................. 62
2.6.3 Capital Structure and Firm Performance ........................................................ 65
2.6.4 Corporate Governance, Regulatory Compliance and Firm Performance ....... 66
2.6.5 Corporate Governance, Capital Structure and Firm Performance .................. 67
2.6.6 Corporate Governance, Capital Structure, Regulatory compliance and Firm
Performance .................................................................................................... 68
2.7 Summary of Empirical Literature and Research Gaps ............................................... 72
2.8 The Conceptual Framework ........................................................................................ 78
2.9 Research Hypotheses .................................................................................................. 79
CHAPTER THREE: RESEARCH METHODOLOGY ............... .............................. 81
3.1 Introduction ................................................................................................................. 81
3.2 Research Philosophy ................................................................................................... 81
3.3 Research Design.......................................................................................................... 83
3.4 Target Population and Sampling ................................................................................. 85
3.5 Data Collection ........................................................................................................... 85
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3.6 Operationalization of Variables .................................................................................. 86
3.7 Reliability and Validity Considerations ...................................................................... 89
3.8 Data Analysis .............................................................................................................. 89
3.8.1 Measurement of firm performance ................................................................. 92
3.8.2 Corporate Governance Index (CGI) ................................................................ 94
3.8.3 Relating the Variables ..................................................................................... 95
CHAPTER FOUR: DESCRIPTIVE ANALYSIS AND RESULTS ........................... 96
4.1 Introduction ................................................................................................................. 96
4.2 Tests of Statistical Assumptions ................................................................................. 96
4.3 Descriptive Statistics ................................................................................................. 100
4.4 Correlation Analysis ................................................................................................. 145
CHAPTER FIVE: DISCUSSION OF FINDINGS..................................................... 147
5.1 Introduction ............................................................................................................... 147
5.2 Corporate Governance and Firm performance ......................................................... 147
5.3 Corporate Governance and Capital Structure ........................................................... 153
5.4 Capital Structure and Firm Performance .................................................................. 155
5.5 Moderating Effect of Regulatory Compliance on firm Performance ....................... 160
5.6 Intervening effect of capital structure on the relationship between corporate
governance and firm Performance ............................................................................ 166
5.7 Joint effect of capital structure and regulatory compliance on the relationship between
corporate governance and firm Performance. .......................................................... 170
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5.8 Discussion of the hypotheses tests and research findings ......................................... 174
5.8.1 The influence of CG on firm performance ................................................... 174
5.8.2 The effect of CG on capital structure ............................................................ 177
5.8.3 The effect of capital structure on firm performance ..................................... 178
5.8.4 The moderating effect of regulatory compliance on the relationship between
CG and firm performance ............................................................................ 179
5.8.5 The intervening effect of capital structure on the relationship between CG and
firm performance ......................................................................................... 180
5.8.6 Joint effect of capital structure and regulatory compliance on the relationship
between CG and firm performance ............................................................... 182
5.9 Summary of Research Findings ................................................................................ 183
CHAPTER SIX: SUMMARY, CONCLUSIONS AND RECOMMENDATIO NS . 185
6.1 Introduction ............................................................................................................... 185
6.2 Summary ................................................................................................................... 185
6.3 Conclusions ............................................................................................................... 187
6.4 Contribution to knowledge ....................................................................................... 190
6.5 Limitations of the study ............................................................................................ 192
6.6 Recommendations and Policy Implications .............................................................. 193
6.7 Suggestions for Future Research .............................................................................. 195
REFERENCES .............................................................................................................. 197
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APPENDICES ............................................................................................................... 211
APPENDIX I: Data Capture Form: Regulatory Compliance Index ............................... 211
APPENDIX II: Data Capture Form: Corporate Governance Index (CGI) ..................... 214
APPENDIX III: Firms Listed At Eac Securities Exchanges .......................................... 218
APPENDIX IV: Data Assumptions ................................................................................ 222
APPENDIX V: Data Summary 2009-2013 At Eacse ..................................................... 238
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LIST OF TABLES
Table 2.1: Summary of Empirical Literature Review ....................................................... 73
Table 3.2: Summary of Research Variables ..................................................................... 87
Table 3.3: Summary of Research Objectives, Hypotheses, Analytical Methods, Statistical
test and Interpretation ...................................................................................... 90
Table 4.4: Results of Tests of Statistical Assumptions (Test of regression assumption and
statistic used) .................................................................................................... 98
Table 4.5: Descriptive statistics results of the main variables included in the model .... 101
Table 4.6: Board Structure and Composition (Kenya-NSE) .......................................... 103
Table 4.7: Board Structure and Composition (Tanzania-DSE) ...................................... 106
Table 4.8: Board Structure and Composition (Uganda-USE) ........................................ 108
Table 4.9: Board Structure and Composition (Rwanda-RSE) ........................................ 110
Table 4.10: Ownership and Shareholding (Kenya-NSE) ................................................ 112
Table 4.11: Ownership and Shareholding (Tanzania-DSE) ........................................... 114
Table 4.12: Ownership and Shareholding (Uganda-USE) .............................................. 116
Table 4.13: Ownership and Shareholding Rwanda-RSE ................................................ 118
Table 4.14: Transparency, Disclosures and Auditing (Kenya-NSE) .............................. 120
Table 4.15: Transparency, Disclosures and Auditing (Tanzania-DSE) .......................... 122
Table 4.16: Transparency, Disclosures and Auditing (Uganda-USE) ............................ 124
Table 4.17: Transparency, Disclosures and Auditing (Rwanda-RSE) ........................... 126
Table 4.18: Board Remuneration (Kenya-NSE) ............................................................. 128
Table 4.19: Board Remuneration (Tanzania-DSE) ......................................................... 131
Table 4.20: Board Remuneration (Uganda-USE) ........................................................... 132
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Table 4.21: Board Remuneration (RWANDA-RSE)...................................................... 134
Table 4.22: Corporate Ethics (Kenya-NSE) ................................................................... 135
Table 4.23: Corporate Ethics (Tanzania-DSE) ............................................................... 137
Table 4.24: Corporate Ethics (Uganda-USE) ................................................................. 138
Table 4.25: Corporate Ethics (Rwanda-RSE)) ................................................................ 140
Table 4.26: Overall Corporate Governance Index (2009-2013) ..................................... 142
Table 4.27: Capital structure, regulatory compliance and firm performance ................. 144
Table 4.28: Correlation Analysis Results ....................................................................... 145
Table 5.29: Effect of corporate governance on ROA ..................................................... 148
Table 5.30: Effect of corporate governance index on Tobin’s Q ................................... 150
Table 5.31: Effect of corporate governance on Cost of capital ...................................... 152
Table 5.32: Relationship between corporate governance and capital structure .............. 154
Table 5.33: Effect of capital structure on ROA .............................................................. 156
Table 5.34: Effect of capital structure on Tobin Q ......................................................... 158
Table 5.35: Effect of capital structure on cost of capital ................................................ 159
Table 5.36: Regression results of the moderating effect of RC on the relationship between
CG and ROA ................................................................................................. 162
Table 5.37: Regression results of the moderating effect of RC on the relationship between
CG and Tobin Q ........................................................................................... 164
Table 5.38: Regression results of the moderating effect of RC on the relationship between
CG and COC ................................................................................................ 165
Table 5.39: Regression results of ROA on capital structure and corporate governance 167
Table 5.40: Regression results of Tobin Q on capital structure and corporate
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governance .................................................................................................... 168
Table 5.41: Regression results of COC on capital structure and corporate governance . 170
Table 5.42: Regression results of the independent, intervening and moderating variable
on ROA ......................................................................................................... 171
Table 5.43: Regression results of the independent, intervening and moderating variable
on Tobin Q .................................................................................................... 172
Table 5.44: Regression results of the independent, intervening and moderating variable
on COC ........................................................................................................ 173
Table 5.45: Summary of Research Objectives, Hypotheses and Test Results................ 184
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LIST OF FIGURES
Figure 2.1: Conceptual Model .......................................................................................... 79
Figure 4.2 Corporate Governance Indicators per Securities Exchange .......................... 141
Figure 4.3 Corporate Governance Index per Country .................................................... 143
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CHAPTER ONE
INTRODUCTION
1.1 Background of the Study
Corporate Governance (CG), Capital Structure (CS) and Regulatory Compliance (RC)
play a big role in the maximization of shareholders’ wealth and good CG is important in
increasing the market value of a firm while higher financial leverage decreases a firm
value by increasing bankruptcy risk (Sheifer and Vishny, 1997). Sound CG governance
mechanisms help assure investors that they will get their capital back and receive an
adequate return on their investment. Firms with good CG provide transparent disclosures
and are investor friendly therefore are able to access capital markets on better terms. A
well-developed financial system provides a market for corporate control while a strong
legal system protects investors’ contractual rights by minimizing the risk of loss from
managerial opportunism. CG is defined as the system by which business corporations are
directed and controlled (Cadbury, 1992), and it encompasses rules as well as the
framework of relationships and processes designed to ensure that directors act in the
interest of the company. An optimal capital structure is the debt/equity ratio for the firm
that minimizes the cost of financing and reduces the chances of bankruptcy.
There has been a great deal of empirical work providing evidence that CG, corporate
financial decisions and firm performance are affected by the presence of agency conflicts
between managers and shareholders. CG activities enhance the efficiency and
effectiveness of organizations with the help of proper supervision and control; thereby
playing a very important role in aligning the interest of shareholders and management to
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reduce agency conflicts (Shleifer and Vishny, 1997). With sound governance structure, it
is much easier for organizations to obtain loans from investors as a functional corporate
structure protects the interest of shareholders, increases transparency and reduces the
agency conflicts. Firms with poor governance practices face more agency problems as
managers of those firm’s can easily obtain private benefits due to poor CG structure.
According to the free cash flow theory, CS acts as strong mechanism to reduce the
agency problem hence reducing the agency costs of free cash flow and if the interests of
managers are not aligned due to the absence of strong CG, they tend to prefer lower than
optimal leverage, hold large amounts of cash and hence exhibit significant
underperformance. Accordingly, several elements of firms’ board structure, ownership
structure and corporate financial policies have been suggested as potential mechanisms to
control for agency problems arising from dispersed ownership (Jensen, 1986). The study
integrates CG theories as well as the CS theories; the agency theory evaluates the role of
the monitoring to reduce agency costs and conflict while capital structure theories
discusses the potential of the debt/equity mix to maximize the value of the firm.
However, despite the substantial evidence on the influence of CG on firm performance
prior research has focused mainly in developed countries where the capital markets are
well developed. In an attempt to provide more insight in the study variables, the research
seeks to evaluate the effect of CS and RC on the relationship between CG and firm
performance of firms listed at East African community exchanges (EACSE), which
includes capital markets in Kenya, Tanzania, Uganda, Burundi and Rwanda. The study
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therefore evaluates the effects of the variables in an emerging economy which have
different CG characteristics, CS, and RC requirements that are unique.
1.1.1 Corporate Governance
CG is the system by which companies are directed and controlled. It specifies the
distribution of rights and responsibilities among different participants in the corporation,
such as the board, managers, shareholders and other stakeholders, and spells out the rules
and procedures for making decisions on corporate affairs. It also provides the structure
through which company objectives are set and monitoring performance attained (OECD,
1999).
Craig (2005) stated that CG is defined and practiced in different ways globally depending
upon the relative power of owners, managers and provider of capital. It entails the
procedures, customs, laws and policies that affect the way corporations are directed,
administered or controlled. An important objective of CG is to ensure accountability and
transparency for those who are involved in the policy implementation of organizations
through mechanisms that will reduce principal agent conflict. Keasey and Wright (1993)
define CG as a framework for effective monitoring, regulation and control of companies
which allows alternative internal and external mechanisms for achieving the laid down
objectives. The internal mechanisms include the board composition, managerial
ownership, and non-managerial shareholding including the institutional shareholding
while external mechanisms includes; the statutory audit, the market for corporate control
and stock market evaluation of corporate performance. Using the agency theory approach
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(Shleifer and Vishny, 1997) define CG as a process in which suppliers of finance to firms
assure themselves of getting a return on their investment. The authors posit that CG is
mainly concerned with principal agency problem between ownership and control and it is
seen as a set of mechanisms through which outside investors protect themselves against
expropriation by insiders. CG is also defined as the system by which companies are
directed and controlled to attain the goals as well as the objectives. It is a set of
relationship between the company’s management, its board, its shareholders and
stakeholders that provides the structure through which objectives of the company are set
and achieved (Cadbury, 1992).
According to Denis (2001) the fundamental perception and understanding of the field of
CG originated from the fact that there are potential problems associated with separation
of ownership and control which was inherent in the modern corporate form of
organization and as a result they viewed CG as a structure with a set of institutional and
market mechanisms that induce self-interested managers to maximize the value of the
residual cash-flow of the firm on behalf of its shareholders. Jensen and Meckling (1976)
stated that the agency theory apply to modern corporation and they explained that a
manager who owns anything less than 100 percent of the residual cash-flow rights of the
firm will tend to have conflict of interest with outside shareholders.
OECD (2004) stated that CG served as one of the main elements in improving economic
efficiency, growth and enhanced investor confidence. It provides a proper incentive for
the board and management to pursue objectives that are in the interest of the company
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and its shareholder and to enhance effective monitoring. The availability of an effective
CG assists in providing a degree of confidence that is necessary for proper functioning of
the market economy.
Pati (2005) stated that the boards and managers are accountable for pursuing effective
CG. The role of effective CG is of great significance for society as whole and it enhances
the efficient use of scarce resources both within the organisation and larger economy, and
therefore there is flow of resources to those sectors where there is efficient production of
goods and services and the return is adequate to satisfy the demand of the stakeholders. It
assists the managers to remain focused on enhancing performance and ensure they are
replaced if they fail to perform. CG forces the organisation to comply with laws and
regulations in the corporate environment, and helps the supervisors to regulate the
economy objectively without favouritism and nepotism. In addition, effective CG
enhances the confidence of investors, which encourages them to invest in those economic
systems which are doing well. It also decreases the risk of capital flight from an economy
and increases the flow and variety of capital in the economy and as a result, the cost of
financing is lower therefore firms are encouraged to use resources more efficiently,
thereby underpinning growth. CG has become such a prominent topic in the past two
decades and it has attracted worldwide attention because of its apparent importance,
particularly due to the much-unexpected collapse of giant corporations like Enron, and
WorldCom (OECD, 2004).
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There is no one model of CG that works in all countries and all companies. Indeed, there
exist many different codes of best practices that take into account differing legislation,
board structures and business practices in individual countries. However, there are
standards that can apply across a broad range of legal, political and economic
environments. With this in mind, OECD (2004) has articulated a set of core principles of
CG practices that are relevant across a range of jurisdictions namely: Fairness,
Transparency, Accountability and Responsibility. These same principles can be used as
cornerstones in a Corporate Governance Index (CGI). In recent years researchers have
explored whether CG as a whole, either viewed as multiple rating factors or as measured
by a composite score is related to firm performance. Gompers et al. (2003) constructed a
CGI to proxy for the level of shareholder rights. The CGI was constructed from factors in
the Investor Responsibility Research Center (IRRC) database and the study focused on
CG provisions related to takeover defenses.
1.1.2 Capital Structure
CS refers to the way a corporation finances its assets through a combination of equity and
debt. The landmark studies of Modigliani and Miller (1958; 1963) about CS irrelevance
and tax shield advantage paved way for the development of other theories. According to
Jensen and Meckling (1976) a firm's optimal CS will involve the trade-off among the
effects of corporate and personal taxes, bankruptcy costs and agency costs.
The separation of ownership and control in a professionally managed firm may result in
managers exerting insufficient work effort, indulging in perquisites, choosing inputs or
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outputs that suit their own preferences, or otherwise failing to maximize firm value. In
effect, the agency costs of outside ownership equal the lost value from professional
managers maximizing their own utility, rather than the value of the firm. Theory suggests
that the choice of CS may help mitigate these agency costs. Under the agency costs
hypothesis, high leverage or a low equity/asset ratio reduces the agency costs of outside
equity and increases firm value by constraining or encouraging managers to act more in
the interests of shareholders (Harris and Raviv, 1991 and Myers, 2001). Greater financial
leverage may affect managers and reduce agency costs through the threat of liquidation,
which causes personal losses to managers’ salaries, reputation, and perquisites and
through pressure to generate cash flow to pay interest expenses (Jensen, 1986).
According to the trade-off approach balancing the advantages and disadvantages of debt,
it would be possible to determine an optimal level of indebtedness that could reduce the
COC and contribute to the creation of economic value. An element of balance is
introduced in CS decisions because of the optimal combination of debt and equity. Firms
that use debt can take advantage not only of tax benefits deriving from the deductibility
of financial obligations, but can also minimize their costs arising from information
asymmetries and discipline managerial behaviour with regards to firm investment
policies. This type of financing, however, also brings with it the possibility that some
specific problems that are attributable to financial distress, agency costs and costs
deriving from a loss of financial flexibility (Myers, 1984).
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The connection between CS and governance seems to emerge when analyzing the costs
and benefits of debt. Under the pecking order approach it is evident that active role of
management in how the firm’s financial resources are used follows an order of preference
and it makes sure that there are no intrusions in its governance activities and also reduces
costs of transaction and information asymmetry. The pecking order theory reflects the
important role that management has in making decisions that aim at protecting survival
and self-sufficiency. According to the pecking order approach, there is no optimal
strategy that can cover financial needs and as a consequence CS would simply be the
result of sedimentation of financing choices made earlier (Harris and Raviv, 1991).
According to Jensen (1986) debt financing ensures that managers promote only those
projects that can guarantee earnings that are sufficient to cover the debt payments. Debt
represents an indirect means of control and discipline of management behaviour by
constraining the tendency to use operational cash flow on personal interest or in an
inefficient manner, in that interest payments and capital payoffs must be taken care of
first.
The important contribution offered by CS as a variable that can explain the connection
between CG and firm performance in controlling opportunistic behaviour in the
economic relations between shareholders, debt holders and managers is not directed at
the explicit cost of debt or equity, but extends also to the relation between investment
policy and CG. CS can influence firm value and performance by limiting conflicts of
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interest that can emerge between shareholders and debt holders and the costs related to
distress and bankruptcy (Bhagat and Jefferis, 2002).
1.1.3 Regulatory Compliance
RC plays a significant role in determining the success of a CG system and a good CG is
more likely to be associated with countries that have a strong legal system. CG
encompasses rules and regulations as well as the framework of relationships and
processes designed to ensure that the Board of Directors (BOD) acts in the interest of the
company and shareholders. The regulatory and CG framework influences the way boards
function and how effective the board engage with the company shareholders. The
regulatory framework for companies in EAC countries are centred on the Company’s
Act, Capital Markets Authority Act and securities exchange regulations of the respective
countries. The Companies Act is the principal legislation regulating companies and it
includes the framework surrounding the formation and duties of directors. The listing
rules deal with the requirements for listing and quotation, market information, trading and
supervisory matters. These rules apply to all companies listed at the securities exchanges.
The Codes of Corporate Governance (CCG) compliments the statutory law requirements
and it gives guidelines on reporting and encourages a “comply or explain” type of
reporting. EAC countries have adopted codes of CG that have borrowed presumably from
more developed countries. EAC countries have legislations that govern CG, regulatory -
bodies overseeing the securities exchanges, and have developed codes of best practice.
Countries have different governance codes that serve as templates for practice in the
concerned countries. They have different set of norms and rules governing the
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composition and the role of the BOD. In some countries, the aspects of the governance
codes are voluntary, but most publicly listed firms tend to satisfy all these conditions and
this is attributed to the market forces that coerce these into best practice codes and firms
adopt them in an effort to gain legitimacy (Stulz et al., 2004).
According to Klapper and Love (2004) CG takes various forms as a result of differences
in the structure of corporate organizations in difference countries especially in the area of
regulation by the state and various professional bodies, the ownership structure, control,
board composition and structure tend to be different. The CG structure relies on the legal,
regulatory, and institutional environment. Moreover, factors like business ethics and
corporate awareness of the environment and societal interest of the communities in which
the company is operating can also affect its reputation and the long- term success. In
addition, CG is also affected by the relationships among those that are involved in the
governance system, controlling shareholders, which can be individuals, family holding
block alliance, cross shareholding, and other companies acting through a holding
company. Creditors play the role of external monitors on corporate performance, while
employee and other stakeholders contributing to the long-term success and performance
of the company and the role of the government create the overall institutional and legal
structure for corporate performance. The law, regulation, voluntary adaptation all play a
part and the most important is the market forces. OECD (2004) revealed that supervisory,
regulatory and enforcement authorities should have the authority, integrity, and resources
to fulfil their duties in a professional and objective manner. Moreover, their rulings
should be timely, transparent and fully explained. Winter (2002) explained that in US,
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the Enron failure brought a number of legislative initiatives like the Sarbanes-Oxley Act
of 2002. The main motivation was to coordinate and strengthen CG through the
improvement of shareholder protection and restoring confidence in the system.
“Comply or explain” is a regulatory approach used in the field of CG and financial
supervision. Rather than setting out binding laws, regulators set out codes which listed
companies may either comply with, or if they do not comply, explain publicly why they
do not. The purpose of “comply or explain” is to let the market decide whether a set of
standards is appropriate for individual companies. Since a company may deviate from the
standard, this approach rejects the view that "one size fits all", but because of the
requirement of disclosure, market investors anticipates that if investors do not accept a
company's explanations, then investors will sell their shares, hence creating a "market
sanction", rather than a legal one (Cadbury,1992).
1.1.4 Firm Performance
Firm performance in the literature is based on the value of the firm. CG affects value as a
result of reduced expropriation by insiders and improvement in the expected cash flow
that can be distributed to investors (Black et al., 2006). To evaluate performance, it is
necessary to determine the constituents of good performance using performance
indicators. To be useful, a performance indicator must be measureable, relevant and
important to the organization (Oakland 1989). Financial performance used in empirical
research on CG fit into both accounting-based measures and market-based measures. The
most commonly used accounting-based measures include the return on assets (ROA)
12
while the most commonly used market-based measure includes the Tobin Q (Baysinger
and Butler, 1985). In order to analyze the relationship between the variables, firm
performance was measured by ROA, Tobin’s Q and Cost of capital (COC).
Short and Keasey (1999) indicated that Tobin’s Q is a market-based measure, which is
the ratio of market value equity plus total liabilities to total assets. It is named after Nobel
Prize Laureate James Tobin and it compares the market value to replacement value of a
firm’s assets. An estimate of the numerator of Tobin’s Q is the book value of assets
minus the book value of common equity plus the market value of common equity. The
denominator is the book value of assets. The study used Tobin’s Q to evaluate the effect
of CG on firm performance. ROA on the other hand is used to measure operating
performance based on the shareholders equity and it explains the efficiency of the
management. ROA shows how profitable company’s assets are in generating revenue. It
is given by the ratio between net income and total assets. It indicates the unit amount of
earning derived from each unit of assets used. It is a useful in comparing competing
companies in the same industry (Black et al., 2006).
While the most common proxies for firm performance are the market and accounting
measures, however there is an emerging brand of idea that a firm’s performance can be
viewed from the perspective of the ability of the firm to benefit from a reduced COC
because of robust CG mechanisms. Robust CG mechanisms lead to lower firm risk and
subsequently to a lower COC, which implicitly increases a firm’s market value. Value is
created when the firm is able to enjoy a cheaper source of capital. COC is also very
13
important for a firm in order to assess future investment opportunities and to re- evaluate
existing investments. COC includes the cost of equity (COE) and cost of debt (COD).
COD is mainly associated with the possibility of default and availability of credible
information for accurately estimating the default risk. A debt holder evaluates the
effectiveness of firms’ CG mechanisms in the assessment of risk profiles when estimating
default risk. Debt holders perceive strong CG as a mechanism to reduce default risk,
which enables them to accept reduction in their risk premium. The willingness of debt
holders to accept this reduction in itself creates value for the firm (Donker and Zahir,
2008).
1.1.5 East African Community Securities Exchange
There are currently four securities exchanges forming the East African Community
Securities Exchange (EACSE) market namely the Nairobi Securities Exchange (NSE),
Dar es Salaam Stock Exchange (DSE), Uganda Securities Exchange (USE) and Rwanda
Stock Exchange (RSE). NSE was formed in 1954 and it is one of the active capital
markets in Africa and the largest in East Africa and there are 61 companies listed at this
exchange. The DSE was incorporated in September 1996 as a private limited company
and it has 16 listed companies. The USE was launched in June 1997, is run under the
jurisdiction of the Capital Markets Authority, which reports to the Central Bank of
Uganda and it has 16 listed companies. The Rwanda Stock Exchange (RSE) is the
youngest exchange in EAC, having opened for business on 31st January 2011. The RSE
took over from the operations of the Rwanda over the Counter Exchange (ROTCE),
which began business in bond trading in January 2008. There are 5 companies listed at
14
RSE. Burundi does not have a security exchange and firms finance their financial needs
through commercial banks (CMA 2012).
The EAC countries have developed and gazetted the guidelines for good CG practices for
listed companies and this was in response to the growing importance of governance
issues both in emerging and developing economies and for promoting growth in domestic
and regional capital markets. It is also in recognition of the role of good governance in
corporate performance, capital formation and maximization of shareholders value as well
as protection of investor’s rights. The development of the guidelines took into account
work that had been undertaken extensively by several jurisdictions through many task
forces and committees including OECD and the Commonwealth Association for
Corporate Governance (CACG). CG best practices are essential for public companies and
it helps to maximise shareholders value through effective and efficient management of
corporate resources. The best practices as per the code are; those practices that relate to
the board of directors, the chairman and CEO, accountability and the role of audit
committees. The board of directors should assume a primary responsibility of fostering
the long-term business of the corporation consistent with their fiduciary responsibility to
the shareholders. The board of directors should accord sufficient time to their functions
and act on a fully informed basis while treating all shareholders fairly and the board of
directors of every listed company should reflect a balance between independent, non-
executive directors and executive directors. Every public listed company should as a
matter of best practice separate the role of the chairman and chief executive in order to
15
ensure a balance of power and authority and provide for checks and balances (Mwangi et
al. 2014).
In Kenya, CG has been gaining root due to the initiatives by stakeholders such as the
NSE in collaboration with the CMA. The Private Sector Corporate Governance Trust
(PSCGT) pointed out that there is an increasing acceptance of CG practices by companies
in the country. Notwithstanding the above developments it must be indicated that more
formal CG structure and institutions are relatively not widespread though number of laws
provide for governance structures for companies in Kenya and these laws include the
companies act and the CMA Act (Mwangi et al. 2014).
In Uganda, CMA guidelines contain minimum standards of CG for public companies and
issuers of debt. The guidelines cover best practices relating to boards, the position of
chairperson and chief executive, rights of shareholders, conduct of general meetings,
accountability and the role of audit committees. This development in the regulatory
framework of the CMA was prompted by the growing importance of governance issues
both in emerging and developing economies and for promoting domestic and regional
capital markets growth. The objective of these guidelines is to strengthen CG practices by
listed companies in Uganda and promote the standards of self-regulation so as to bring
the level of governance in line with international trends. CMA (2006) found that efforts
that have been made by various organizations, like Bank of Uganda, the Institute of CG
of Uganda, and the CMA to improve the CG system. The CMA conducted a survey of
compliance level of seven listed companies by using the data from annual report of those
16
companies. It found that there is need for better clarity when providing for corporate
information, and there is need for improvement in degree of reporting and most
companies provide generic information (USE, 2014).
In Tanzania the Capital Markets and Securities Authority (CMSA) was established in
1994 to regulate securities business, promote a security market and establish the stock
exchange. The Dar es Salaam stock exchange (DSE) was established in 1996. However,
the stock market is still in early stages in development. CMSA have issued CG guidelines
that apply to the public listed companies. The Rwanda Stock Exchange (RSE) has only
four companies listed, while there is no stock exchange in Burundi, and capital is raised
mainly from commercial banks. The guidelines contain principles generally agreed upon
within the East Africa Securities Regulatory Authorities (EASRA), Kenya, Uganda and
Tanzania has common law systems while Rwanda and Burundi have a civil law system
(CMA, 2006).
1.2 Research Problem
The impact of CG on firm performance has been a subject of great empirical
investigations in finance. CG has been part of research in business economics since
Adam Smith’s 1776 seminal publication of an inquiry into the nature and causes of the
wealth of nations and undoubtedly given impetus through classic publication of the
separation of corporate ownership from control (Berle and Means, 1932). The separation
of ownership and control in a firm may result in managers exerting insufficient work
effort, indulging in perquisites, choosing inputs or outputs that suit their own preferences,
17
or otherwise failing to maximize firm value. In effect, the agency costs of outside
ownership equal the lost value from professional managers maximizing their own utility,
rather than the value of the firm. CG and the choice of capital structure may help mitigate
these agency costs. CG is an important factor in improving the value and performance of
the firm and the impact differs country to country because of different structures resulting
from dissimilar social, economic, and regulatory conditions. CS also has different
impacts on the value of the firm country to country because of the different regulations.
The collapse of major corporations such as Enron, WorldCom and the Bank of Credit and
Commerce International (BCCI) in the UK and US has stimulated the recent interest in
CG. The Asian economic crisis also has contributed to the raising profile of CG. In the
EAC, governance has been debated in the context of state ownership of corporations
where corruption, mismanagement and government subsidization of failing enterprises
have been the defining features. There has been an attempt to address CG challenges in
EAC by the privatization policy and the capital markets authorities. There has also been a
worldwide effort to improve the effectives of CG. These include the OECD and CACG
which have led to the development of principles for effective CG. The issues that have
stimulated interests in the phenomenon of CG, point to particular causes of governance
crises. These include weak legal and regulatory systems, inconsistent accounting and
auditing standards, and poor banking practices. Thin and poorly regulated capital
markets, ineffective oversight by corporate boards of directors, and little regard for the
rights of minority shareholders are also problems with respect to CG (World Bank,
2000).
18
Measuring firm performance has been another element of debate in CG research: profits,
prices and rates of return are the most popular measures of performance. Profitability
however depends on many factors outside the direct control of firms and may not be a
true measure of firm performance that can be attributable to firm specific characteristics.
Only in recent years, that researchers have begun to investigate the impact of CG
mechanisms on the other dimension of firms’ performance that is the COC and it is
argued that if firms are able to enjoy cheaper cost of raising capital therefore a value has
been created for the shareholders (Donker and Zahir, 2008). Pham et al., (2011) found
that CG mechanisms play an important role in explaining a firm’s COC. It shows that
greater insider ownership, the presence of institutional block holders and independent
boards serve to reduce the perceived risk thereby leading investors to demand lower rates
of return on capital provided.
Aduda and Musyoka (2011) evaluated the relationship between executive compensation
and firm performance in the Kenyan banking industry between 2004 and 2008. The study
found a negative relationship between executive compensation and the bank size and this
was attributed to the diminishing influence of key owners as the bank grows in size. The
study did not consider the moderating effects of other variables on the relationship
between CG and firm performance. Lishenga (2012) also evaluated the effect of board
meetings as proxy for CG on firm performance. The study found that the frequency of
board meetings increases following poor performance and as a consequence of such
meetings performance of firms improved because frequency of board meetings allows for
19
better communication between management and directors. The study only considered one
CG governance mechanism and did not consider the effects of CG when measured as an
index incorporating all the variables.
Ongore and K’Obonyo (2011) did a study on CG and firm performance among the listed
companies at NSE. The study evaluated the relationship between ownership
concentration and firm performance, and the findings revealed that there is a significant
relationship between ownership concentration and firm performance as measured by
ROA and ROE. However, the study did not consider any moderating or intervening
variables in the relationship between CG and Firm Performance. CS can influence
performance by limiting conflicts of interests that can emerge between shareholders and
debts holders while CG encompasses rules and regulations that ensure that BOD acts in
the best interest of the company and shareholders (Bhagat and Jeffers, 2002).
The above studies yielded mixed results and also did not consider the combinative effect
of CS and RC on the relationship between CG and firm performance. Most of the studies
were done in developed economies therefore contextual differences may yield different
results thus findings and conclusions of these studies may not apply to firms operating in
the East African community context. Some of the studies also utilized small samples,
while the current study used a large sample which comprised all the firms listed at the
East African community exchanges. No known study has focused on the moderating,
intervening and the joint effect of CG, CS, RC and firm performance. Specifically, the
study investigated the influence of CS and RC on the relationship between CG and firm
20
performance. The study therefore attempted to answer the research question, what is the
effect of capital structure and regulatory compliance on the relationship between CG and
performance of firms in EACSE?
1.3 Research Objectives
The broad objective of this study is to investigate how capital structure and regulatory
compliance affect the relationship between corporate governance and firm performance:
i. To examine the effect of corporate governance on firm performance among the listed
companies in East African Community Securities Exchange.
ii. To evaluate the effect of corporate governance on capital structure among companies
listed at the East African Community Securities Exchange.
iii. To determine the effect of capital structure on firm performance among the listed
companies in the East African Community Securities Exchange.
iv. To establish the moderating effect of regulatory compliance on the relationship
between corporate governance and firm performance among the companies listed at
the East African Community Securities Exchange.
v. To determine the intervening effect of capital structure on the relationship between
corporate governance and firm performance among the companies listed at the East
African Community Securities Exchange.
vi. To establish the joint effect of capital structure and regulatory compliance on the
relationship between corporate governance and firm performance among the
companies listed at the East African Community Securities Exchange.
21
1.4 Value of the Study
This study provides an additional insight into the influence of capital structure and
regulatory compliance on the relationship between CG and firm performance. It is hoped
that the study will provide important quantitative information into CG and add to the
existing body of empirical literature from developing securities exchanges such as that of
Kenya, Uganda, Tanzania, Rwanda and Burundi.
This study also considered the combinative effects of capital structure, regulatory
compliance, and how these variables affect the relationship between CG and firm
performance, whereas other researchers have focused on the separate effects of these
variables. This study will shed light on the importance of corporate governance, capital
and regulatory compliance; hence companies will put in place good CG mechanisms.
The study contributes to theory and practice in finance in that the thesis link the literature
on CG and firm performance by considering capital structure and regulatory compliance
as moderating and intervening variables respectively. Good CG is argued to positively
impact on performance. But what is the best proxy of performance to measure CG. It is
therefore necessary to use several proxies of performance i.e. ROA, Tobin Q and COC.
The results of this study have important implications for managers of firms, private
individuals as well as institutional investors, regulators and directors on corporate boards.
CG disclosure is required not only by investors, but also by creditors, employees,
regulatory agencies and by the public at large. Increased demand for capital and a
growing investment community have complicated the managing of corporations.
22
Managers’ decisions concerning CG thus need to be guided by a set of best practices.
From a practitioner’s point of view, the study will shed light on best practices in CG
activities of EAC listed companies.
23
CHAPTER TWO
LITERATURE REVIEW
2.1 Introduction
The chapter begins with a discussion of the theories in which the study is grounded and
then follows a review of literature highlighting relationships between the various
variables of the study, the summary of gaps in knowledge from the empirical studies
reviewed is provided as well as the conceptual framework depicting the relationship
between the variables of study.
2.2 Theoretical Foundation
The theoretical framework upon which CG, CS and RC is based includes the agency
theory, stakeholder theory, stewardship theory, institutional theory, political theory,
Modigliani-miller theorem, trade-off theory and free cash flow theory. Evidence from
previous empirical studies has sought to confirm the effect of CG on firm performance
and reviewed the theories.
2.2.1 Agency Theory
CG has traditionally been associated with the “principal-agent” or “agency” paradox. A
“principal-agent” relationship arises when the person who owns a firm is not the same as
the person who managers or controls it. Agency theory has its roots in economic theory
and was developed by Jensen and Meckling (1976) and it states that shareholders who are
the owners or principals of the company delegate the running of business to the managers
24
or agents. The shareholders expect the agents to act and make decisions in the principal’s
interest but the agents may make contrary decisions.
The agency model of corporations is the implicit presumption that the conflicts are
between strong entrenched managers and weak dispersed shareholders. This has led to an
almost exclusive focus, in both the analytical work and in reform efforts of resolving the
monitoring and management entrenchment problems, which are the main CG problems.
There are three types of separation of ownership and control. The first is majority control
where some of the shareholders own majority of shares, and the minority shareholders is
widely diffused and are separated from control. The second is minority control, where
ownership is widely spread and the greater part of ownership is practically without
control. The third is management control where the directors or managers are responsible
in controlling the corporation. The separation of ownership and control has resulted in
divergence of interests between shareholders and the managers.
Jensen and Meckling (1976) argued that the separation of ownership and control has
resulted in an agency problem as the managers who act as agents might not always act in
the best interests of the shareholders or owners, who are the principals of the firm. This
might be due to the interests of both parties which are not aligned. Agency problem
results in agency costs, which are the costs of the separation of ownership and control.
Agency costs have been defined as the sum of the monitoring expenditures by the
principal, the bonding expenditures by the agent and the residual costs. The agency
problems arise because managers will not solely act to maximize the shareholders’
25
wealth; they may protect their own interests or seek the goal of maximizing companies’
growth instead of earnings while making decisions. Jensen and Meckling (1976)
suggested that the inefficiency may be reduced as managerial incentives to take value
maximizing decisions increased. Agency costs arise from divergence of interests
between shareholders and company managers; it includes the monitoring costs, bonding
costs, residual loss and costs of free cash flow and debt
Monitoring costs are expenditures paid by the principal to observe and control an agent’s
behaviour. The economic impact of asymmetric information also results in various
corporate agency problems. Firm managers (insiders) know more about their firm than
shareholders and debt financiers (outsiders). When outsiders are unable to judge over the
firm's performance, they tend to qualify a firm’s performance as moderate. A result of
this asymmetric information is that shares of a firm with a great performance are
undervalued and vice versa. More specifically, information asymmetries between
shareholders or bondholders and corporate executive management creates the necessity of
monitoring (costs) and complications for the structuring of financial contracts. They may
include the costs of preparing reliable accounting information and audits, writing
executive compensation contracts and even ultimately the cost of replacing managers.
Denis (2001) contended that effective monitoring is restricted to certain groups or
individuals. Such monitors must have the necessary expertise and incentives to fully
monitor manager. In addition, such monitors must provide a credible threat to
management’s control of the company. To minimize monitoring costs, managers tend to
26
set up structures and try to act in shareholder’s best interests. The costs of establishing
and adhering to these systems are known as bonding costs. They may include the costs of
additional information disclosures to shareholders. Agents will stop incurring bonding
costs when the marginal reduction in monitoring equals the marginal increase in bonding
costs. As suggested by the agency theory, the optimal bonding contract should aim to
entice managers into making all decisions that are in the shareholder’s best interests.
However, since managers cannot be made to do everything that shareholders would wish,
bonding provides a means of making managers do some of the things that shareholders
would like by writing a less than perfect contract.
Despite monitoring and bonding, the interest of managers and shareholders are still
unlikely to be fully aligned. Therefore, there are still agency losses arising from conflicts
of interest. These are known as residual loss, which represent a trade-off between overly
constraining management and enforcing contractual mechanisms designed to reduce
agency problems. There are three groups of participants in a firm, suppliers of equity, debt
suppliers and firm managers. It is logical that they would try to achieve their goals with
different measures. Suppliers of equity, or shareholders, are interested in high dividend
ratio’s and high share prices. Debt suppliers, on the other hand, are interested in interest
and debt repayments, whereas firm managers would be focused on their financial
remuneration. These conflicts of interest give rise to opportunity costs and inspection
costs. These costs decrease the market value of a firm. Kim and Sorensen (1986)
investigated the presence of agency costs and their relation to debt policies of
corporations. It is found that firms with higher insiders (managers) ownership have greater
27
debt ratios than firms with lower insider ownership, which may be explained by the
agency costs of debt or the agency costs of equity.
The principal-agent model is probably the most important model of CG, because the
shareholders’ residual voting rights commit the corporate resources to value
maximization. According to Jensen and Meckling (1976), the relationship between the
owners and the management involves the delegation of some decision-making authority to
the agent by the principal. One critique of the agency approach is that the analytical focus
on how to resolve CG problem is too narrow and the shareholders are not the only ones
who make investments in the company therefore CG will be affected by the relationships
among the various stakeholders in the firm.
2.2.2 Stakeholder Theory
The stakeholder theory derived from a combination of the sociological and organizational
disciplines. It is less of a formal unified theory and more of a broad research tradition,
incorporating philosophy, ethics, political theory, economics, law and organizational
science. Stakeholder theory was embedded in the management discipline in 1970 and
gradually developed by Freeman (1984) incorporating corporate accountability to a broad
range of stakeholders.
Unlike agency theory in which the managers are working and serving the shareholders,
stakeholder theorists suggest that managers in organizations have a network of
relationships to serve and this include the suppliers, employees and business partners. In
28
addition, it was argued that this group of network is important other than owner-manager-
employee relationship as in agency theory. Sundaram and Inkpen (2004) contend that
stakeholder theory attempts to address the group of stakeholders deserving and requiring
management’s attention. The groups participate in a business to obtain benefits and the
relationships with many other groups can affect decision making processes as stakeholder
theory is concerned with the nature of these relationships in terms of both processes and
outcomes for the firm and its stakeholders.
CG systems are in a state of transition due to internationalization of capital markets,
resulting in convergence of the shareholder value-based approach to CG and the
stakeholder concept of CG towards sustainable business systems (Clarke ,1998). It can be
seen that stakeholder theory is an extension of the agency perspective, where
responsibility of the board of directors is increased from shareholders to other
stakeholders’ interests (Smallman, 2004). Therefore, a narrow focus on shareholders has
undergone a change and is expected to take into account a broader group of stakeholders
such as those interest groups linked to social, environmental and ethical considerations
(Freeman et al., 2004).
Criticisms that focus on stakeholder theory identify the problem of who constitutes
genuine stakeholders. One argument is that meeting stakeholders’ interests also opens up
a path for corruption, as it offers agents the opportunity to divert the wealth away from
the shareholders to others (Smallman, 2004). But the moral perspective of stakeholder
theory is all stakeholders have a right to be treated fairly by an organization, and
29
managers should manage the organization for the benefit of all stakeholders, regardless of
whether the stakeholder management leads to better financial performance (Deegan,
2004). Another critique of the stakeholders’ model is that managers may use stakeholder
reasons to justify poor performance and also it provides an inadequate explanation of the
firm’s behavior within its environment.
2.2.3 Stewardship Theory
Stewardship theory grew out of the seminal work by Donaldson and Davis (1991) and
was developed as a model where senior executives act as stewards for the organization
and in the best interests of the principals. The theory asserts that managers will make
decisions and act in the best interest of the firm, putting collectivist options above self-
serving options. Notably, stewards are motivated only by making the right decisions
which are in the best interest of the organization, as there is strong assumption that
stewards will benefit, if the firm prospers. At the same time, stewardship theory presumes
that executives and managers’ main duty is to maximize firm performance, while
working under the premise that both principal and stewards benefits from the
performance of the organization.
Daily et al. (2003) augured that in order to protect their reputations as decision makers in
organizations, executives and directors are inclined to operate the firm to maximize
financial performance as well as shareholders’ profits. In this sense, it is believed that the
firm’s performance can directly impact perceptions of their individual performance. The
30
executives and directors are seen as effective stewards of their organization if they return
finance to investors to establish a good reputation.
Stewardship theory has been framed as the organizational behaviour counterweight to
rational action theories of management. It holds that there is no conflict of interest
between managers and owners, and that the goal of governance is to find the mechanisms
and structure that facilitate the most effective coordination between the two parties.
Stewardship theory holds that there is no inherent problem of executive control, meaning
that organizational managers tend to be benign in their actions (Donaldson, 2008). The
essential assumption underlying the prescriptions of stewardship theory is that the
behaviours of the manager are aligned with the interests of the principals. The theory
places greater value on goal convergence among the parties involved in CG than on the
agent’s self-interest.
The theory is mainly concerned with identifying the situations in which the interests of
the principal and the steward are aligned (Donaldson and Davis, 1993). According to this
theory, there are situational and psychological factors that predispose individuals to
become agents or stewards. The situational factors refer to the surrounding cultural
context, rather than to an organization’s work environment. Some of the situational
factors that predispose an individual towards stewardship are working in an involvement-
oriented management system, as opposed to a control-oriented management system; a
collectivistic culture, as opposed to an individualistic one; a low-power distance culture;
or when CG structures give them authority and discretion (Donaldson and Davis, 1993).
31
According to Davis et al., (1997), the process through which the parties decide to be
agents or stewards can be synthesized as follows: First, this is a decision made by both
parties of the relationship. Second, the psychological characteristics and the cultural
background of each party predispose the individuals to make a particular choice. And
finally, the expectation that each party has about the other will influence the choice
between agency or stewardship relationships. Davis et al., (1997) remain silent, however,
about the specific interactions of antecedents in the prediction of stewardship versus
agency theory. When the factors that surround the individual, both psychological and
situational, are aligned to make him decide to be a steward or agent, the situation is clear
as there is no conflict inside the person. The problem arises when there are conflicting
forces between the psychological and the situational factors
The theory assumes that that becoming a steward or an agent is the result of a rational
process. In this rational process, the individual evaluates the pros and cons of one
position versus the other. There are contributions in stewardship literature that argue that
stewards are not altruistic, but that there are situations where executives perceive that
serving shareholders’ interests also serves their own interests. In this situation, agents
would recognize that the company’s performance directly impacts perceptions of their
individual performance. In other words, in being effective stewards of the organization,
they also manage their own careers (Daily et al., 2003).
32
2.2.4 Institutional Theory
Institutional theory is a widely accepted theoretical posture that emphasizes organizations
is social cultural systems and it focuses on the deeper and more resilient aspects of social
structure. It considers the processes by which structures, including schemes; rules, norms,
and routines as authoritative guidelines for social behaviour (Scott, 2004). Different
components of institutional theory explain how these elements are created and adapted
over time.
The emphasis on institutional theory is normally viewed from the regulatory perspective.
Better legal environment encourages the adoption of good CG practices due increased
incentives to the firms and countries have different governance codes that serve as
templates for practice in the concerned countries (Stulz et al., 2004). The main idea of
institutional theory is that the organizations are exposed and linked to external
environment accordingly; CG should ensure that, there is a clear link between the
organizations and environment based on organizations goals and objectives. CG should
have an effective influence and involvement in formalizing and identifying corporate
goals. Cohen et al. (2007) suggested that, in order to formulate a compensation policy
senior manager should understand all norms and traditions of the organization. However,
those policies are resistant to change even in the face of major changes in job content and
technology complexity. The adaptation and rejection of these changes should be
examined and investigated based on the historical, social and political issues that are
linked to recognizing organizational changes.
33
According to Weir et al. (2002) CG consists of external governance mechanisms and
internal governance mechanisms that are linked to the concept of institutional theory. The
theory explains the deeper and more resilient aspects of social structure, processes,
schemes, rules, norms and routines that have become established as authoritative
guidelines for social behavior. It looks at how these elements are created, diffused,
adopted and adapted over space and time, and how they fall into decline and disuse.
Basically, institutional theory asserts that organizational structures and procedures are
adopted because important external institutions prefer them. Institutional networks are
not merely control and co-coordinating mechanisms for economic transactions, they
socially construct rules and beliefs for conformity and reward.
2.2.5 Political Theory
Political theory brings the approach of developing voting support from shareholders,
rather by purchasing voting power. Hence having a political influence in corporations
may direct CG within the organization. Public interest is much reserved as the
government participates in corporate decision making, taking into consideration cultural
challenges (Pound, 1992). The political model highlights the allocation of corporate
power, profits and privileges are determined via the governments’ favour. The political
model of CG can have an immense influence on governance developments. Over the last
decades, the government of a country has been seen to have a strong political influence
on firms. As a result, there is an entrance of politics into the governance structure or
firms’ mechanism.
34
The relation between firm performance and CG has been the subject of extensive
research in the past recent years. Most of the related empirical literature examines the
relation between firm performance and some sub-set of many dimensions of governance
such as board size, board composition, executive compensation, insider ownership, and
anti-takeover provision.
2.2.6 The Modigliani-Miller Theorem
The theory of business finance in a modern sense starts with the Modigliani and Miller
(1958) capital structure which assumes that the firms have a particular set of expected
cash flows. When the firm chooses a certain proportion of debt and equity to finance its
assets, all that it does is to divide up the cash flows among investors. Investors and firms
are assumed to have equal access to financial markets, which allows for homemade
leverage. The investor can create any leverage that is wanted but not offered, or the
investor can get rid of any leverage that the firm took on but was not wanted. As a result,
the leverage of the firm has no effect on the market value of the firm. Their paper led
subsequently to both clarity and controversy. As a matter of theory, capital structure
irrelevance can be proved under a range of circumstances.
The classic arbitrage-based irrelevance propositions provide settings in which arbitrage
by investors keeps the value of the firm independent of its leverage. The second
irrelevance proposition concludes that “given a firm’s investment policy, the dividend
payout it chooses to follow will affect neither the current price of its shares nor the total
return to its shareholder” (Miller and Modigliani, 1963), in other words, in perfect
35
markets, neither capital structure choices nor divided policy decisions matter. The 1958
paper stimulated serious research devoted to disproving of irrelevance as a matter of
theory or as an empirical matter. The most commonly used elements include
consideration of taxes, transaction costs, bankruptcy costs, agency conflicts, adverse
selection, lack of reparability between financing and operations, time-varying financial
market opportunities, and investor clientele effects. Harris and Raviv (1991) stated that
the Modigliani-Miller irrelevance proposition is not easy to test. With debt and firm value
both plausibly endogenous and driven by other factors such as profits, collateral, and
growth opportunities, they didn’t establish a structural test of the theory by regressing
value on debt. But the fact that fairly reliable empirical relations between a number of
factors and corporate leverage exist, while not disproving the theory, does make it seem
an unlikely characterization of how real businesses are financed.
While the Modigliani-Miller theorem does not provide a realistic description of how
firms finance their operations, it provides a means of finding reasons why financing may
matter and this description provides a reasonable interpretation of much of the theory of
corporate finance. Accordingly, it is influenced the early development of both the trade-
off theory and the pecking order theory.
2.2.7 Trade-Off Theory
The debate on capital structure started with propositions demonstrated by Modigliani and
Miller (1958; 1963). At first, in the absence of corporate tax and bankruptcy costs, they
concluded that firm value is independent of its capital structure. Later, they came out with
36
other conclusions, in the existence of corporate tax; firm value will increase if the firm
increases its leverage. Hence, they argued that the optimal debt level will be met based on
the trade-off between tax advantage of debt offset by the increased risk in bankruptcy and
agency costs of debt.
The optimal debt-equity ratio is the point at which firm value is maximized (Jensen,
1993). The firm value is independent of its capital structure and there is no optimum debt
ratio for any individual firm suggesting that there is a tax advantage of using debt.
Theoretically, Stulz (1990) found that leverage is positively correlated with firm value
and that capital structure can be used to reduce agency costs and as a result increase firm
value.
2.2.8 Free Cash Flow Theory
According to free cash flow theory (Jensen, 1986), leverage itself can also act as a
monitoring mechanism and thereby reduces the agency problem hence increasing firm
value by reducing the agency costs of free cash flow. There are some consequences
derived if a firm is employing higher leverage level in that managers of such firm will not
be able to invest in non-profitable new projects, as doing so the new projects might not be
able to generate cash flows to the firm, hence managers might fail in paying the fixed
amount of interest on the debt or the principal when it’s due. It also might cause the
inability to generate profit in a certain financial year that may result in failing to pay
dividends to firm shareholders. Furthermore, in employing more leverage, managers are
forced to distribute the cash flows, including future cash flows to the debt holders as they
37
are bonded in doing so at a fixed amount and in a specified period of time. If managers
fail in fulfilling this obligation, debt holders might take the firm into bankruptcy case.
This risk may further motivate managers to decrease their consumption of perks and
increase their efficiency. Jensen (1986) stated that from the agency view, the higher the
degree of moral hazard, the higher the leverage of the firm should be as managers will
have to pay for the fixed obligation resulting from the debt hence; it will reduce
managers’ perquisites. Extensive research suggests that debt can act as a self-enforcing
governance mechanism; that is, issuing debt holds managers’ “feet to the fire” by forcing
them to generate cash to meet interest and principle obligations (Gillan, 2006)
Leverage might not only be able to reduce the agency costs of free cash flow, but also can
increase the efficiency of the managers. This is due to the debt market that might function
as a more effective capital market monitoring. In addition, in order to obtain the debt
financing, managers must show their abilities and efficiencies in managing the firm.
Empirically, it has been proven that leverage proxied by bank lenders, can be substitute
monitoring mechanism especially in weak CG firms, but not in the more active merger
environments. In conclusion, this theory suggests that leverage is vital in playing its role
as monitoring mechanism. This is due to the higher the leverage level, the higher the
probability of bankruptcy, and when this happens, managers might lose their jobs. As
such it might motivate managers to work harder in order to avoid this risk by fulfilling
the fixed obligation to the debt holders. In addition, as a consequence, it will reduce the
managers’ perquisites as they will be pressured not to waste the firm cash flows. This
also will increase the efficiency of managers in making decisions especially in selecting
38
new profitable projects. All of these consequences will increase the firm value. Hence,
these consequences will make the interests of owners and managers aligned. This might
be the reason why owners or shareholders prefer high leverage level, which is contradict
to managers, as managers want to avoid the consequences derived in employing more
leverage. In this situation, ownership concentration can play its role in forcing managers
to choose higher leverage level.
2.2.8 Summary of Theoretical Foundation
Agency theory focuses on the conflicting interests between the principals and agents
while stakeholder theory explores the dilemma regarding the interests of different groups
of stakeholders. Stewardship theory underscores the importance of the board as stewards
and envisages a role beyond their traditional control responsibility considered from the
agency theory perspective. Institutional theory is based upon the notion that better legal
environment encourages the adoption of good CG practices and political theory brings
the approach of developing voting support from shareholders, rather by purchasing voting
power. Modigliani-miller theorem, trade-off theory and the free cash flow theory
evaluates the effect of leverage as a monitoring mechanism which increases the
efficiency of the managers.
2.3 Internal Corporate Governance Mechanisms
Internal governance mechanisms refer to the extent to which particular internal
mechanisms is concerned with the systems and practices adopted by the organizations.
The mechanisms are largely inter-dependent in that the success depends on the holistic
39
adoption of all those factors. Internal governance mechanisms are, nevertheless only one
component of effective and robust CG. As such internal governance mechanisms need to
be aligned and complementary to external governance mechanisms. The internal CG
includes; the board size, the board independence, executive compensation, frequency of
board meetings, financial policy, ownership concentration and CEO duality (Daily and
Dalton, 1992).
2.3.1 Board of Directors
Most organizations are governed by board of directors (BOD) which is an important
institution in the governance of modern corporations. Having a board is one of the legal
requirements for incorporation. BOD in theory helps to solve agency problems inherent
in managing an organization. Although board satisfy numerous regulatory requirements
their economic function is determined by the organizational problems they help to
address. The major conflict within the boardroom is between the CEO and the directors.
The CEO has incentives to influence the board so that he keeps his job and increase other
benefits (Hermalin and Weisbach, 2003)
Dalton and Daily (1999) outlined three widely recognized functions of boards of
directors, namely the control, service and resource dependence roles. Most literature on
the control function of the board draws on agency theory, which emphasizes the
separation of ownership (shareholders) and control (professional managers) inherent in
modern corporations. From an agency theory perspective, boards represent the primary
internal mechanism for controlling managers’ opportunistic behaviour, thus helping to
40
align shareholders’ and managers’ interests. Service role entails directors giving expert
views and strategic advice to the CEO while the resource dependence perspective views
the board as an instrument for sourcing critical resources and information to create
sustainable competitive advantage.
2.3.2 Board size
Board size refers to the total number of BOD of an organization and it includes the CEO
and Chairman. The board size also includes the number of outside directors, executive
directors and NED (Bhagat and Black 2002). The directors are elected by the
shareholders at the AGMs and they do retire depending on the Company’s Memorandum
of Association. There is no restriction on the number of board members stipulated under
the OECD Code on Corporate Governance although the board is required to include a
balance of executive and non-executive directors to avoid the board being dominated by
one individual. However under the best practices in corporate governance (Finance
Committee on Corporate Governance, 2000) it is recommended that every board examine
its size so as to ensure optimum effectiveness.
There is a view that larger boards do better in regards to corporate performance because
they have a range of expertise to help make better decisions, and are harder for a
powerful CEO to dominate however, recent thinking has leaned towards smaller boards.
Lipton and Lorsch (1992) argue that large boards are less effective and are easier for the
CEO to control and also when a board gets too big, it becomes difficult to manage and
co-ordinate. Eisenberg et al. (1998) found that smaller board reduce the possibility of
41
free riding and increases the accountability of individual directors. They also stated that
there is a negative correlation between board size and profitability when using sample of
small and midsize companies, which suggests that board-size effects can exist even when
there is less separation of ownership and control in these smaller firms.
2.3.3 Board Independence
Though the issue of whether directors should be employees of or affiliated with the firm
(inside directors) or outsiders has been well researched, no clear conclusion has been
reached. On one hand, inside directors are more familiar with the firm’s activities and
they can act as monitors to top management if they perceive the opportunity to advance
into positions held by incompetent executives. On the other hand, outside directors may
act as “professional referees” to ensure that competition among insiders stimulates
actions consistent with shareholder value maximization (Fama, 1980).
However, there appears no evidence that insider/outsider ratio is correlated with firm
performance (Hermalin and Weisbach, 2001) found that firms with more independent
directors achieved improved firm profitability. Baysinger and Butler (1985) advocated
for a mix of insiders and outsiders on the board and found empirical support that this
approach enhances firm performance. Agrawal and Knoeber (1996) suggest that boards
expanded for political reasons often result in too many outsiders on the board, which does
not help performance.
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2.3.4 CEO duality
Chief executive officer (CEO) duality refers to the situation when the CEO also holds the
position of the chairman of the board. The BOD monitors the managers such as the CEO
on the behalf of the shareholders and they design compensation contracts which also
entail the details on hiring and firing the top executive. A dual CEO benefits the firm if
he or she works closely with the board to create value. Establishing a unity of command
at the head of the firm allows the firm to send a reassuring message to shareholders.
However, it is also easier for the CEO to assert control of the board and consequently
make it more difficult for shareholders to monitor and discipline the management
(Jensen, 1993).
Daily and Dalton (1992) found no relationship between CEO duality and performance in
entrepreneurial firms. They argued that board leadership structure depends entirely on
individual firm characteristics such as organizational complexity, availability of other
controls over CEO authority and CEO reputation and power. Using a sample of 2,166
U.S. companies, they found that companies with complex operations (implying need for
CEO to make swift actions), alternative control mechanisms and sound CEO reputation
are more likely to have CEO duality.
2.3.5 Interlocking directorates
Interlocking directorate occurs when a person from one organization sits on the board of
directors of another company and in the most stringent definition, when current senior
managers and/or directors of two companies simultaneously serve on each other’s boards.
43
Interlocking directorates exist for class integration, defined as the mutual protection of
the interests of a social class by its members. Two firms have a direct interlock if a
director or executive of one firm is also a director of the other, and an indirect interlock if
a director of each sits on the board of a third firm. This practice, although widespread and
lawful, raises questions about the quality and independence of board decisions (Useem,
1982).
Interlocking directorates is resource dependence whereby directors could exchange
resources, e.g. capital, industry information, and market access to buffer the effects of
environmental uncertainty. Interlocks designed to protect a managerial class have a priori
implication for firm performance while those designed to reduce environmental
uncertainty could potentially increase the efficient deployment of resource and hence
enhance firm performance (Pfeffer and Salancik 1978).
2.3.6 Frequency of board meetings
Vafeas (1999) found that the annual number of board meetings increases as share price
declines and operating performance of firms improves following years of increased board
meetings. This suggests meeting frequency is an important dimension of an effective
board.
Lipton and Lorsch (1992) find that the most widely shared problem directors face is lack
of time to carry out their duties, and that board meeting time is an important resource in
improving the effectiveness of a board. Yet, an opposing view is that board meetings are
44
not necessarily useful because the limited time the outside directors spend together is not
used for the meaningful exchange of ideas among themselves or with management
(Jensen, 1993), a problem that is a by-product of the fact that CEOs almost always set the
agenda for board meetings.
2.3.7 Board Diversity
Keys et al. (2003) found significant evidence of a positive relationship between board
diversity, proxied by the percentage of women and/or minority races on boards of
directors, and firm value, measured by Tobin’s Q. Firms making commitment to
increasing the number of women on boards also have more minorities on their boards and
vice versa, and that the fraction of women and minority directors increases with firm size
but decreases as the number of inside directors increases.
Hermalin and Weisbach (2001) contended that board- specific phenomena are not quite
explained by principal-agent models and note that current theoretical framework
including agency theory does not provide clear-cut prediction concerning the link
between board diversity and firm value. On the other hand, firms have in recent years
been increasingly pressured by institutional investors and shareholder activists to appoint
directors with different backgrounds and expertise, under the assumption that greater
diversity of the boards of directors should lead to less insular decision making processes
and greater openness to change. There are also strong conceptual and business
propositions for diversity. A diverse workforce and diverse leadership within the firm can
increase its competitiveness as a great variety of ideas and viewpoints are available for
45
decision- making, attract a larger base of shareholders and employees, and help retain
existing as well as potentially gain new minority consumers.
2.3.8 Director and executive compensation
The directors’ remuneration should be sufficient and competitively structured to attract
and retain directors to run the company effectively and should be approved by
shareholders and it should be linked to performance. NED remunerations should be
competitive and in line with remuneration of other directors in competing sectors,
therefore every company should establish a formal and transparent procedure for
remuneration of directors. The BOD of every listed company should appoint a
remuneration committee or assign a mandate to a nominating committee consisting
mainly of independent and NED to recommend to the board the remuneration of the
executive directors and the structure of their compensation package (CMA 2006).
An often-suggested internal solution to the problem of inefficient or self- serving
management is the development of compensation plans that tie management
compensation directly to firm performance, e.g. through stock price performance. This
pay-for-performance plan generally helps to reduce agency problems in the firm (Morgan
and Poulsen, 2001), as the votes approving the plan are positively related to firms that
have high investment or high growth opportunities. On the other hand, votes approving
the plan are inversely related to negative features in some of the plans such as dilution of
shareholder stakes.
46
2.3.9 Board and managerial ownership
Stulz (1988) established that the cost of large shareholdings and entrenchment predicts a
negative relationship between managerial ownership and firm value. As managerial
ownership and control increase, the negative effect on firm value associated with the
entrenchment of manager-owners starts to exceed the incentive benefits of managerial
ownership. The entrenchment costs of manager ownership relate to a managers’ ability to
block value-enhancing takeovers. Claessens et al. (2002) also found that firm value
increases with the cash-flow ownership (right to receive dividends) of the largest and
controlling shareholder, consistent with “incentive” effects. But when the control rights
(arising from pyramid structure, cross-holding and dual-class shares) of the controlling
shareholder exceed its cash-flow rights, firm value falls, which is consistent with
“entrenchment” effects. La Porta et al. (2002), using samples in 27 wealthy countries,
found evidence in firms with higher cash flow ownership by controlling shareholder
improves firm valuation, especially in countries with poor legal investor protection.
Baek et al. (2004) found evidence that Korean listed firms with concentrated ownership
by controlling family shareholders experienced a larger drop in stock value during the
1997 financial crisis. Using listed firms in eight East Asian economies to study the effect
of ownership structure on firm value.
2.4 External Corporate Governance Mechanisms
An external governance mechanism refers to the components by which actors external to
the management exercise control over the performance of the company. In other words,
47
external governance mechanisms are concerned with the elements by which principals
ensure compliance of agents (McKnight 2002) to the stated and implied objectives of
principals. External governance mechanisms thereby represent obligations on the part of
agents that underpin the intended objectives and performance of principals. External
governance mechanisms are thus concerned with the controls and transparency imposed
by parties outside.
2.4.1 Large block holders
Investors with large ownership stakes have strong incentives to maximize their firms’
value and are able to collect information and oversee managers and that can help
overcome the principal-agent problem (Jensen and Meckling 1976). Large shareholders
also have strong incentives to put pressure on managers or even to oust them through a
proxy fight or a takeover. The large shareholders thus address the agency problem in that
they have both a general interest in profit maximization, and enough control over the
assets of the firm to have their interest respected.
Shleifer and Vishny (1997) found that large investors may represent their own interest,
which need not coincide with the interest of other investors in the firm or with the
interests of employees and managers, and that not all institutional monitoring are
positively related to firm value, as some institutional investors such as administrators of
public pension funds (as opposed to private pension funds) may focus on political or
social issues other than firm performance. Thus, not all shareholders may benefit from
the managerial monitoring by institutional investors.
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2.4.2 Legal system
Corporate regulations come from different sources including: Company Acts, Bankruptcy
Acts, Accounting Standards, and disclosure requirements from stock exchanges. Recent
research suggests that the extent of legal protection of investors in a country is an
important determinant of the development of financial markets. La Porta et al. (2000)
found out that the protection of shareholders and creditors by the legal system is not only
crucial to preventing expropriation by managers or controlling shareholders, it is also
central to understanding the diversity in ownership structure and efficiency of investment
allocation.
La Porta et al. (2002) found evidence of higher valuation, measured by Tobin’s Q, of
firms in 27 wealthy countries with better protection of minority shareholders. This
evidence indirectly supports the negative effects of expropriation of minority
shareholders by controlling shareholders in many countries, and for the role of the law in
limiting such expropriation.
2.4.3 Leverage
Capital structure as measured by leverage shows the relationship between long term
liabilities and shareholders’ equity and it can be used as a powerful tool to improve
performance. Leverage measures the ability of an organization to deal with business
downturns and it implies that a company having a high leverage (gearing ratio) is more
vulnerable to business shocks because it has less ability to service debt. Jensen (1986)
documented that debt has a positive role in motivating organizational efficiency as a way
49
to reduce agency cost relating to free cash flow. Debt creation enables managers to
effectively bond their promise to pay out future cash flows to motivate cuts in expansion
programs and the sale of those divisions that are more valuable outside the firms.
DeAngelo et al. (2002) established that debt covenants and debt maturity can constrain
managerial discretion more effectively than does the pressure to meet cash interest
obligations. They stated that excess liquid assets can be used to satisfy a firm’s short to
intermediate-term cash obligations and buy time without improving operations, whereas
accounting-based debt covenants such as minimum earnings and net worth constraints
require operating improvements. In the same vein, debt contracts with shorter maturities
give managers less scope to buy time by using liquid assets to meet interest payments and
provide more frequent oversight by suppliers of debt capital.
2.5 Corporate Governance Codes
The set of mechanisms guiding good CG decision making has been introduced in recent
years through the enactment of governance codes throughout the world. The corporate
financial scandals have made good CG an important tool for investors and other
stakeholders. The scandals have resulted in countries introducing codes of good
governance to complement their commercial codes or corporate laws and majority of the
codes are voluntary. The principles formulated have provided a broad framework for a
large number of countries to develop their own specific principles of corporate
governance (Monks and Minow, 2002). The broad membership of the OECD and CACG
organizations suggest that these principles reflect the views of a large number of
50
countries with respect to addressing CG. The CG principles are minimum benchmarks
against which member countries can compare their systems and carry out country-
specific initiatives (OECD, 1999).
Turnbull (1999) noted that although the principles are important, their limitations need to
be recognized. She posits that these principles, which carry notions of codes of best
practice, can be misleading. The codes tend to be portraying that they are ethically correct
and righteous. She further points out that even if companies follow these principles, there
is still no assurance to the shareholders that the business is either a good investment or
ethical. Therefore these principles should be understood as minimum acceptable practices
as this will alert investors to the possibility of superior governance standards.
2.5.1 The OECD principles for effective corporate governance
The principles for effective corporate governance issued by the OECD in 1999 and
updated in 2004 are organized under five headings which includes;1) ensuring the basis
for an effective corporate governance framework, 2) the rights of shareholders, 3)
equitable treatment of all shareholders, 4) the role of stakeholders in corporate
governance, 4) disclosure and 5) the responsibility of the board of directors. The first
principle, introduced in the revised set of principles released in 2004, addresses the
corporate governance framework and institutional structures. This principle was treated
separately in the revised set of principles, and requires countries to promote transparent
and efficient markets, the rule of law and clearly articulate the division of responsibilities
among different supervisory, regulatory and enforcement authorities (OECD, 2004). The
51
principle requires a CG framework to be developed with a view of its impact on the
overall market participants and the promotion of transparent and efficient markets. The
principle largely appears to encourage accountability among those institutions that have a
bearing on CG. A clear division of responsibilities among authorities is needed to ensure
that the public interest is served. The issue of resources and the integrity of supervisory,
regulatory and enforcement authorities are also articulated in this principle.
The principles of good CG recognize the property right of shareholders and attempt to
explicate them: the rights to secure methods of ownership, convey or transfer shares,
obtain relevant information on the corporation on a timely and regular basis, participate
and vote at general meetings, elect members of the board and share in the profits of the
corporation. Embedded in the rights of shareholders is the concept of ownership of the
corporation by its shareholders. The right to information about the corporation is aimed
at facilitating decision making with respect to control of the corporation. The
buying/selling of shares reflects the acknowledgement of the control that can be exercised
through the market for corporate control and presupposes the existence of such a market.
These encourage member countries to remove barriers to the transferability of shares and
other restrictions that hamper the operation of the market for corporate control. This
reflects the Anglo-Saxon view of corporate governance. Participation in the election of
the board requires transparent procedures that permit shareholders to elect directors who
will protect and advance their interests. This is also reflective of the traditional Anglo-
Saxon view of corporate governance in which directors are considered as agents of
shareholders. In general this principle is aligned with the liberalist’s perspective of
52
corporate governance in which shareholders are sovereign and are entitled to exercise
ultimate control over corporations. However, there is a weakness inherent in this
principle: mentioning the extensive rights is not the same as effective corporate
governance (Frederick, 1999).
2.5.2 CACG principles of effective corporate governance
The CG principles are aimed at realizing a number of outcomes including an
improvement in the profitability and efficiency of Commonwealth countries’ business
enterprises; improving the capacity to create wealth and employment; and ensuring the
long-term competitiveness of Commonwealth countries in the global market place, the
stability and credibility of the Commonwealth financial sectors both nationally and
internationally (CACG, 1999).
These principles are also concerned with the relationship between business enterprises
and their various stakeholders: shareholders, managers, employees, customers, suppliers,
labor unions, communities, and providers of finances. The board of directors is focused
upon, in the CACG principles of corporate governance, as the principal mechanism for
addressing corporate governance issues. These principles reflect the shareholders’
supremacy as the primary beneficiaries of corporate activity and as a legitimate
constituency. The issues that come into consideration in the CACG principles are similar
to those considered under the OECD set of principles of corporate governance which are
broader in scope. Since the one-tier board system is acknowledged in member countries,
the independence of the board is of paramount importance. The mix of directors
53
recommended, i.e. a combination of executive and non-executive directors are reflective
of this position. A leadership structure, as an important aspect underlying board
effectiveness in the control function, is also advocated (CACG, 1999).
2.5.3 Corporate governance codes in East African Countries
CG guidelines for good governance practices for listed companies in East African
Securities Exchange have been developed by the respective authorities and this was in
response to the growing importance of governance issues both in emerging and
developing economies, and for promoting growth in domestic and regional capital
markets. It is also in recognition of the role of good governance in corporate
performance, capital formation and maximization of shareholders value as well as
protection of investor’s rights. The regulatory authorities developed the guidelines by
taking into account the work which had been undertaken extensively by several
jurisdictions through many task forces and committees included but not limited to the
UK, Malaysia, South Africa, OECD and the CACG.
CG best practices are essential for public companies in that it helps to maximise
shareholders value through effective and efficient management of corporate resources.
The best practices as per the code are; those practices that relate to the board of directors,
the chairman and CEO, accountability and the role of audit committees. The BOD
assumes the primary responsibility of fostering the long-term business of the corporation
consistent with their fiduciary responsibility to the shareholders. The BODs should
accord sufficient time to their functions and act on a fully informed basis while treating
54
all shareholders fairly and the BODs of every listed company should reflect a balance
between independent, NED and executive directors. Every public listed company should
as a matter of best practice separate the role of the chairman and CEO in order to ensure a
balance of power and authority, and provide for checks and balances. Prior to CMA’s
promulgation of the guidelines for good CG, the Private Sector Corporate Governance
Trust (PSCGT), Kenya issued a code of best practice for CG and most of the provisions
in this code were incorporated in the CMA’s guidelines (PSCGT, 1999).
2.5.4 Models of Corporate Governance
The CG structure of a given country is determined by several factors: the legal and
regulatory framework outlining the rights and responsibilities of all parties involved, but
the CG provisions may differ from corporation to corporation. In each country, the CG
structure has certain characteristics which distinguish it from structures in other countries.
To date, researchers have identified three models of corporate governance in capital
markets. These are the Anglo-US model, the German model, and the Japanese model
The Anglo-US model is characterized by the dominance in the company of independent
persons and individual shareholders. The manager is responsible to the BOD and
shareholders, the latter being especially interested in profitable activities and received
dividends. It ensures the mobility of investments and their placement from the inefficient
to the developed areas. The Anglo-US model is characterized by share ownership of
individuals and increasingly institutional investors defining the rights and responsibilities
of management, directors and shareholders (Jeffers, 2005).
55
According to Mallin (2006) the German model is characterized by a high concentration
of shareholders who have common interests with the organization and participate in its
management and control. Managers are responsible to a wider group of stakeholders,
besides shareholders, such as unions and business partners. Ownership and control of
listed companies are significantly concentrated, shareholders having the opportunity of
intervention in the management process. In this model of governance, the enterprise is
seen as the combination of various interest groups aimed to coordinate the national
interest objectives. From a historical point of view, German banks have played an
important role in corporate decisions. A great importance is given to the protection of
creditors, even to the point where a bank might dominate a firm. In the model, CG system
provides information and encourages employees to participate in various activities of the
enterprise.
The Japanese model brings together industrial groups consisting of companies with
common interests and similar strategies. The managers’ responsibility manifests itself in
relations with shareholders and keiretsu (a network of loyal suppliers and customers).
Keiretsu represents a complex pattern of cooperation and also competition, characterized
by the adoption of defensive tactics in hostile takeovers, reducing the degree of
opportunism of parties involved and keeping long term business relationships. The
characteristic pattern of governance is dominated by two types of legal relationships: one
of co-determination between shareholders and unions, customers, suppliers, creditors,
government and the other is ratio between administrators and those stakeholders,
56
including managers. The necessity of the model results from the fact that the activity of a
company should not be upset by the relations between all these people (Jeffers, 2005).
2.6 Empirical Studies
2.6.1 Corporate Governance and Firm Performance
The study builds on the agency theory by Jensen and Meckling (1976) who evaluated the
relation between the principal and the agent. The principals who are the owners hire the
agents to manage the firm and they may not necessary make decisions that are in the best
interest of the owners. The value decreasing activities by the managers’ decreases
profitability therefore CG plays an important role in enhancing firm value by reducing
such activities. Shleifer and Vishny (1997) also indicated that better-governed firms are
more likely to invest in profitable projects, resulting in more efficient operations and
higher expected future cash flows.
Yermack (1996) considered the effect of the number of directors on firm performance. In
a sample of 452 large U.S. public corporations observed over the period 1984 to 1991, he
found an inverse relation between firm market value, as represented by Tobin’s Q, and
the size of the board of directors as a proxy for CG. The association appears in both
cross-sectional analyses of the variation among firms and in time-series analyses of the
variation within individual companies. The negative relation between board size and firm
value decreases as boards become large, implying that the greatest incremental costs arise
as boards grow in size from small to medium. The loss in firm value when boards grow
57
from six to 12 members is estimated to be equal to the value lost when boards grow from
12 to 24. Very few boards have fewer than six or more than 24 directors.
Hermalin and Weisbach (2001) conducted a study on the relationship between board
composition and board size on firm performance. They focused on one of the board tasks
of hiring and firing CEOs. Board independence depends on the bargain between the
board and the CEO. The CEO prefers a less independent board while the board prefers to
maintain its independence. Firms have been pressured by institutional investors and
shareholder activists in the recent years to appoint directors with different backgrounds
and expertise, under the assumption that greater diversity of the BODs should lead to less
insular decision making processes and greater openness to change. A diverse workforce
and leadership within the firm can increase its competitiveness as a great variety of ideas
and viewpoints are available for decision- making, attract a large base of shareholders
and employees, and help retain existing as well as potentially gain new consumers. They
concluded that board composition is not related to firm performance, while board size has
a negative relation to corporate performance. Both board composition and size do appear
to be related to the quality of the board’s decisions regards CEO replacement and
executive compensation.
Daily and Dalton (1992) found no relationship between CEO duality and performance in
entrepreneurial firms. They argued that board leadership structure depends entirely on
individual firm characteristics such as organizational complexity, availability of other
controls over CEO authority and CEO reputation and power. Using a sample of 2,166 of
58
U.S. companies, they found that companies with complex operations, alternative control
mechanisms and sound CEO reputation are more likely to have CEO duality.
Aduda and Musyoka (2011) while looking at CG mechanisms among commercial banks
in Kenya found a negative relationship between executive compensation and bank size
and this has been attributed to the diminishing influence of key owners as the bank
grows in size. Performance ratios and opportunity only appear to be inversely related to
big banks, as their executives appear to subordinate their immediate financial interests to
that of the overall goal of the firm, which is to maximize profitability. The emphasis of
the study was the banking sector in Kenya.
According to Lishenga (2012) boards normally increases the frequency of their meetings
following poor performance and as a consequence of such an increase, the performance
of firms improves as captured by the increase in the firms’ value. Frequent meetings
allow for better communication between management and directors. However, frequent
meetings might also distract the firm’s managers from their day-to-day operational
responsibilities. Ongore and K’Obonyo (2011) considered the effects of ownership
structures on performance of listed companies in Kenya. The period of study was only
two years and only a single CG mechanism was considered.
The creation of firm-level CG indices began with Gompers et al. (2003) research, where
they constructed index from data on the governance characteristics of over 1,000 firms.
The sum of the components is the governance index (G-Index) and they found a
59
significant relation between the index and stock returns and Tobin’s Q. CG encompasses
a broad spectrum of internal and external mechanisms intended to mitigate agency risk by
increasing the monitoring of managements’ actions, limiting managers’ opportunistic
behaviour, and improving the quality of firms’ information flows in the context of
separation of ownership and control. Ultimately, CG will be able to induce self-interested
controllers of a firm to make decisions and allocate resources that could maximise the
value of the firm to its owners. It is argued that if firms put in place robust governance
mechanisms they should be well managed and profitable.
Brown and Caylor (2006) tested the significance of CG metrics (governance index) using
data for 2,327 firms; they tested Tobin’s Q of the firm data set as a performance metric
against each of the 51 governance metrics. They hypothesized that a smaller number of
governance factors have the major effect on firm performance. They used an adjusted
data set of 1,868 firms and regressed each of the 51 governance independent variables
against firms’ Tobin’s Q. The authors found that seven of the governance metrics are
related to firms’ Tobin’s Q. Therefore they documented that CG measured by Gov-score
is significantly and positively associated with Tobin Q. The governance provisions that
are linked to firm performance includes; option re-pricing, average option granted,
directors attending 75% of board meetings, board guidelines about proxy statements and
directors stock ownership option.
Black et al. (2006) constructed a Korean CG index for 515 Korean companies, based on a
survey of corporate governance practices in all companies listed on the Korea Stock
60
Exchange in 2001. The authors extracted 38 variables from the survey questions, which
they classified into 4 sub-indices before combining the sub-indices into the overall index.
They reported positive significant relationship between CG to Tobin’s Q.
Drobetz et al. (2004) documented a positive relationship between CG practices and firm
performance in German public firms, based on a broad CG rating related to the German
Corporate Governance code. To construct their sample, they sent questionnaires to 253
German firms in different market segments to which they had a 36% response. They
assume constant historical ratings since their CG data are limited to one observation.
Beiner et al. (2006) sent out a questionnaire based on the suggestions and
recommendations of the Swiss Code of Best Practice, to all Swiss firms quoted on the
Swiss Stock Exchange in 2003. The index consists of 38 governance attributes across 5
categories. They report that at one point increase in the CG index causes an increase in
market capitalization of roughly 8.52%.
Although COC is primarily a risk measure, it is also related to firm value and can be
considered a key determinant of firm’s value other than market and accounting
performance measures. Robust CG mechanisms will lead to lower firm risk and
subsequently to a lower COC, which implicitly increases a firm’s market value. Value is
created when the firm is able to enjoy a cheaper source of capital. In addition, the COC is
very important for a firm in order to assess future investment opportunities and to re-
evaluate existing investments (Donker and Zahir, 2008).
61
Ashbaugh et al. (2004) documented the effect of CG on the COE by linking governance
attributes to firm’s expected returns, beta and realized returns. The governance attributes
used in this research were related to ownership structure, shareholder rights, and board
structure. Huang (2004) also supported this using a sample of 8,836 firms investigated
the effect of firm-level variation in shareholder rights on COE. The shareholder rights is
the ability of shareholders to remove managers and weak shareholder rights indicates that
poorly performing managers are able to entrench themselves, thus raising the COC. Piot
and Missonier-Piera (2007) reported that CG quality and auditing structure of public
firms have a significant reducing effect on the cost of debt. Pham et al., (2011) sampled
large Australian firms from 1994 to 2003, they found that the variation in firm level CG
mechanism plays an important role in explaining a firm’s COC. It shows that greater
insider ownership, the present of institutional block holders and smaller and independent
boards all serve to reduce the perceived risk of firm thereby leading investors to demand
lower rates of return on capital provided. The institutional block shareholders are likely to
independent of management.
Himmelberg et al. (2002) investigated the impact of agency problems on COC by
introducing insider risk aversion as the offsetting cost of insider ownership in their
model. The trade-off between risk and incentives distorts the incentive of insiders to
invest in risky projects. The COC should include a risk premium reflecting insiders’
exposure to idiosyncratic risk. They also assumed that the severity of agency costs
depends on a parameter representing investor protection. In equilibrium, the marginal
62
COC is a weighted average of terms reflecting both idiosyncratic and beta risks, and in
which weaker investor protection increases the weight on idiosyncratic risk.
Himmelberg et al. (1999) further argued that CG and firm performance may be driven by
common firm characteristics, some of which are neither clearly observable nor
measurable. Managers tend to hold large ownership stakes (which is commonly viewed
in the literature as a mechanism to combat agency problems) in high-risk and high-
growth firms to signify their commitment and with the use of equity-based remuneration;
insider ownership may automatically increase after periods of strong performance.
However, this spurious correlation does not offer any insight into the impact of insider
ownership in reducing agency problems and improving firm performance. The results
confirm the results of Cremers and Neir (2005) that both internal and external CG has a
positive significant relationship with firm performance. Thus, the first hypothesis stated
in the null form is:
H1: There is no significant relationship between corporate governance and firm
performance
2.6.2Corporate Governance and Capital Structure
Empirical studies between CG and capitals structure appear to be varied and
inconclusive. According to Lipton and Lorsch (1992), there is a significant relationship
between capital structure and board size. Berger and Lubrano (2006) found that firms
with larger board membership have low leverage or debt ratio. They assume that larger
board size translates into strong pressure from the corporate board to make managers
63
pursue lower leverage or debt ratio rather than have larger boards. Their findings suggest
that large board size which are more entrenched due to superior monitoring by regulatory
bodies, pursue higher leverage to raise company value. Berger et al (1997) argues that
firms with higher leverage rather have relatively more outside directors, while firms with
low percentage of outside directors experience lower leverage.
Capital structure of a company is based on the board of director’s decision and in
compliance to CG code of best practices. According to Hart (1995) there exist a
significant negative relationship between board size and capital structure and opposite
finding on the association between CEO duality and leverage where it implies that larger
boards adopt low debt policy and CEO as the board chairman tend to employ high
proportion of debt. Jensen (1986) explains the benefits of debt in reducing agency costs
of free cash flow, in situations where the firm generates substantial free cash flow making
the conflict of interest among shareholders and managers especially severe.
Debt serves as a bonding or commitment device by reducing the free cash flow available
to managers. In this respect, debt limits inefficiency of management, at least if managers
want to repay the debt. Berger et al. (1997) find that entrenched CEOs seek to avoid debt.
When managers do not experience discipline from CG and control mechanisms,
including monitoring by board, the threat of dismissal or takeover, and compensation-
based performance incentives, managers may prefer less leverage or adjusting it more
slowly since they dislike performance pressures associated with commitment to repay the
debt and interests on it in the future.
64
Berger (1997) finds that firms with larger board of directors generally have low debts
equity levels. He argues that larger boards exert pressure on managers to follow lower
gearing levels and enhance firm performance. Abor (2007) examined the relationship
between corporate governance and capital structure decisions of Ghanaian Small and
Medium Enterprises (SME) by using multivariate regression analysis. The results provide
evidence about negative relationship between board size and leverage ratios and SMEs
with larger boards generally have low level of gearing.
Anderson (2004) found that the COD is generally lower for larger boards because lenders
think that these companies are being monitored more effectively by a diversified portfolio
of experts. So debt financing becomes a cost effective choice. Independent directors are
cornerstone of modern CG. The relationship between presence of independent directors
and capital structure has been explored by few researchers but evidence in this regard is
mixed. According to Pfeffer and Salancick (1978) NED plays a pivotal role in enhancing
the capability of a company to get recognition from external stake holders. Thus leads to
reduction in uncertainty about company and enhance ability of the company to raise
funds. De Miguel and Pindalo (2001) develop a target adjustment model to explain firm’s
debt in terms of its debt in the previous period and its target level of debt, which is a
function of firm characteristics i.e. profitability, growth and assets tangibility. On the
other hand, Wen (2002) found a positive relationship between CG and capital structure.
He argues that large boards follow a policy of higher levels of gearing to enhance firm
value especially when these are entrenched due to greater monitoring by regulatory
65
authorities. It is also argued that larger board may find difficulty in arriving at a
consensus in decision which can ultimately affect the quality of CG and will translate into
higher financial leverage levels. Thus, the second hypothesis stated in the null form is:
H2: There is no significant relationship between corporate governance and capital
structure.
2.6.3 Capital Structure and Firm Performance
Capital structure is the mix of debt and equity capital maintained by a firm, Modigliani
and Miller (1958) stated that an organization financing is of paramount importance to
both the managers of firms and providers of funds. Brigham and Gapenski (1996) argued
that an optimal capital structure can be attained if there exists a tax sheltering benefits
provided an increase in debt level is equal to the bankruptcy costs. They suggested that
managers of the firm should be able to identify when the optimal capital structure is
attained and try to maintain it at that level. This is the point at which the financing costs
and the COC are minimized, thereby increasing firm value and performance.
Jensen and Ruback (1983) argue that managers do not always manage the firm to
maximize returns to shareholders. As a result of this, managers may adopt non-profitable
investments, even though the outcome is likely to be losses for shareholders. They tend to
use the free cash flow available to fulfil their personal interests instead of investing in
positive Net Present Value projects that would benefit the shareholders. Jensen (1986)
argues that the agency cost is likely to exacerbate in the presence of free cash flow in the
firm. In order to mitigate this agency conflict, Pinegar and Wilbricht (1989) argue that
66
capital structure can be used by increasing the debt level and without causing any radical
increase in agency costs. This will force the managers to invest in profitable ventures that
will be of benefit to the shareholders. If they decide to invest in non-profitable projects
and they are unable to pay the interest due to debt holders, the debt holders can force the
firm to liquidation and managers will lose their decision rights or possibly their
employment. Thus, the third hypothesis stated in the null form is:
H3: There is no significant relationship between capital structure and firm performance.
2.6.4 Corporate Governance, Regulatory Compliance and Firm Performance
Company performance is enhanced when regulations and guidelines have been adhered
to. Investors, regulators and other stakeholders clearly consider compliance to be
important (Fasterling, 2005). In addition to regulation, CG practices are also reflected in
different factors such as culture, traditional financial options, corporate ownership
patterns and legal origins (Zattoni and Francesca, 2008). It is generally accepted that the
purpose of regulations concerning CG is not to increase the value of a firm but to enhance
investors’ confidence. Consequently pressure from the regulatory authorities will
encourage firms to comply with voluntary codes of best practice. Bechner and Freyer
(2009) suggest that regulatory compliance and CG act in a complementary manner to
resolve the agency problem. Regulations reduce management dominance in the firm by
increasing the influence of external parties such as auditors and shareholders. Conversely,
deregulation increases the influence of management (Kole and Lehn, 1997).
67
In a regulated environment, the internal control system of firms is expected to be secure,
whereas monitoring costs are higher if the environment is deregulated because firms need
to regularly monitor management activity for the sake of shareholders investment and
return. Therefore, it can be argued that a regulated environment ensures better monitoring
and lower agency costs. Moreover, regulations ensure a unique system or standard in the
economy and enable the comparison of industry level practice, and the business
environment will be unstable in the absence of regulations (Kole & Lehn, 1997).
CG evolved due to the existence of the agency problem associated with the separation of
owners and managers, and regulation can mitigate the conflicts that arise as a result
(Drobetz, 2002). It is generally assumed that a regulatory environment would result in
enhanced CG because companies are meant to comply with the relevant regulations, and
according to Hermalin (2005) regulation has a positive impact on CG hence firm
performance. Thus, the fourth hypothesis stated in the null form is:
H4: There is no significant moderating effect of regulatory compliance on the
relationship between corporate governance and firm performance.
2.6.5 Corporate Governance, Capital Structure and Firm Performance
Capital structure can be analysed not only in purely financial terms but can also be
analysed by looking at the rights and attributes that characterise the firm’s assets and that
influence, with different levels of intensity, governance activities. Equity and debt,
therefore, must be considered as both financial instruments and CG instruments: debt
subordinates governance activities to stricter management, while equity allows for greater
68
flexibility and decision making power. Jensen and Meckling (1976), by making a
distinction between internal and external equity, contextualize the relation between
ownership and capital structures. It can thus be inferred that when capital structure
becomes an instrument of CG, not only the mix between debt and equity and their well-
known consequences as far as taxes go must be taken into consideration. The way in
which cash flow is allocated and, even more importantly, how the right to make decisions
and manage the firm (voting rights) is dealt with must also be examined.
Developments in the agency theory suggest that CG, together with capital structure
decisions, influences firm value, in that it mitigates agency conflicts between managers,
shareholders and debt holders (Putnan 1993). William (1988) evaluated the relation
between debt and equity in terms of CG and firm performance, and affirmed that capital
structure is able to influence management activity and performance. Coase (1991), stated
that it is important to pay more attention to the role of capital structure as an instrument
that can mediate and moderate governance structure within the firm and, consequently,
firm performance. Thus, the firth hypothesis stated in the null form is:
H5: There is no significant intervening effect of capital structure on the relationship
between corporate governance and firm performance.
2.6.6 Corporate Governance, Capital Structure, Regulatory compliance and Firm
Performance
The legal system is an important CG mechanism and there are cross-country differences
to the extent to which countries offer legal protection affect companies. The high level of
69
protection is in inverse proportion to ownership concentration thus CG. Countries with
the highest legal protection have widest shareholder dispersion and conversely,
ownership concentration is highest in countries offering the least protection to minority
investors (La Porta et al., 1998).
Good CG is related to the shareholders rights, transparency and board accountability thus
it embraces standards (laws), principles and best practices (codes) which are important in
cross-country analysis. The set of mechanisms guiding good CG has been introduced
through enactment of governance codes throughout the world. The corporate scandals
have also resulted in countries introducing codes of good governance to complement their
corporate laws. The studies looking at the association between CG and firm performance
in different countries have found contradictory results (Hermalin and Weisbach, 2003).
La portal, et al. (1998) examined the legal rules covering protection of corporate
shareholders and creditors, the origin of the rules and quality of enforcement in 49
countries. Using empirical analysis the result revealed that common law countries have
the strongest, French countries have the weakest, and the German-and Scandinavian-
civil- law countries are at the middle. In addition, the authors found that concentration of
ownership of shares in largest public companies was negatively related to investor
protections, and the same with hypothesis that small, and diversified shareholders are not
likely to be recognized in countries that cannot protect their right. Klapper and Love
(2004) used data on CG ranking in firms across 14 developing markets. Using empirical
evidence the authors found that there was variation in firm- level of governance in the
70
sample and the firm-level of governance was lower in those countries that have weak
legal systems and firm level of corporate governance should take seriously for countries
with weaker legal system. In addition, better CG was correlated with higher operating
performance. Johnson, et al. (1999) empirically used the Asian financial crises to
revealed how legal institution affected corporate governance on the depreciation and
stock market. The authors found that managerial agency problem can make countries
with weak legal system loss the confidence of investor and in a cross-country regression,
corporate governance variables enumerate more of the variation in exchange rate and
stock market performance during the Asian crises than macroeconomic variables. The
author found that the protection of minority shareholder right was one of the main
reasons for depreciation and stock market declines during the crisis.
La portal, et al. (2000) examined the level of protection by law on investors, both
shareholders and creditors from expropriation by the managers and controlling
shareholders of firms. The authors posited that legal approach is the more meaningful
way to understand CG. Furthermore, La portal, et al. (2002) formulated a model of the
effects of legal protection of minority shareholders and of cash-flow ownership by
controlling shareholder on the valuation of firms. The model was tested empirically using
sample of 539 large firms from 27 developed economic countries. The results revealed
that, higher valuation of firms in countries with well protection of minority shareholders,
and firms with higher cash-flow ownership by controlling shareholders and the finding of
this study was consistent with DeAngelo and DeAngelo (1985).
71
Shleifer and Vishny, (1997) examined the importance of legal protection of investor, and
ownership concentration in corporation around the world. They stated that CG deals with
agency problem, the separation of management and capital structure, the question of CG
was how to assure the supplier of capital that they get return on their investment. They
authors proceed forward, by posited that agency problem give an opportunities for the
managers to run away with suppliers of capital fund or used them on irrelevant project
with well documented. In the absent of governance it will be failure, as a result of the
above, legal protection of investors rights, was one of important element of corporate
governance. The concentration ownership through large shareholders, takeover, and bank
financing are general method of control that can help investors to get back their money.
Even though large investors can be assist effectively in providing solution to agency
problem, but they may be inefficient in redistribution of the wealth from other investor to
themselves. Anderson and Gupta (2009) noted that the relationship CG and firm
performance is enhanced when there is an optimal capital structure and an effective legal
system. Using a sample of 1736 unique firms representing 22 countries they found that
there is joint effect of a country’s financial structure and legal system does matter when
explaining the relationship between performance and the overall level of CG in a given
country. Thus, the sixth hypothesis stated in the null form is:
H6: There is no significant joint effect of capital structure and regulatory compliance on
the relationship between corporate governance and firm performance.
72
2.7 Summary of Empirical Literature and Research Gaps
The empirical analysis of the relationship between composite CG mechanisms, capital
structure, regulatory compliance, and firm performance has yet to provide a convincing
causal link among these factors. A reasonable conclusion, based on the prior research, is
that good CG has a positive effect on capital structure, regulatory compliance, and firm
performance but there are other studies that have concluded there is a negative
relationship.
A number of research gaps arise from the analysis of the issues examined in this chapter.
These include firstly, lack of consensus on the effect of CG on firm performance. There
are studies who found a positive relationship between CG and firm performance while
other studies found a negative relationship between the variables. Therefore the results
from the literature are mixed. Secondly most of the studies reviewed only look at just a
few of the CG variables like board size, board composition and structure. Thirdly, most
of the studies have looked at the accounting and market based performance measures.
Fourthly, most of the studies have only looked at the combinative effect of capital
structure and regulatory compliance on the relation between CG and firm performance.
Table 2.1 is a summary of empirical literature, their results, and research gaps and how
the current study addresses these gaps.
73
Table 2.1: Summary of Empirical Literature Review
Researcher(s) Focus of study Study Model/Variables
Findings Research Gaps Addressing the gaps in the current study
Baysinger B.D and
Hoskisson R.R
(1990)
To examine the effect
of NED on firm
performance
The independent
variable was NED
while the dependent
variable was firm
performance(Tobin
Q)
The study looked at the effect
of board independence by
considering discrete tasks
such as replacing the CEO or
defending against a takeover
bid
The research does not
establish a clear
correlation between
board independence
and firm performance
The study is to evaluate
the effect of all CG
mechanisms on firm
performance by using
COC,ROA and Tobin Q
Daily and Dalton
(1992)
The relationship
between governance
structure and CEO
duality , and firm
financial performance
The independent
variable was
governance structure
and CEO duality
while the dependent
variable was firm
performance as
measured by ROA,
ROE and P/E ratios
By using, both accounting
based performance measures
(ROA and ROE) and market
based performance measures
(P/E ratios), they found no
association between CEO
duality and financial
performance.
The study may not be
extended a cross all
companies because it
only used non-
financial companies
as a sample.
The study will consider
all companies that are
quoted at the EAC
exchanges for a period
of 5 years.
Yermack, D.
(1996),
To evaluate the higher
valuation of companies
with small board of
directors in USA
between 1984-1991
Board size and firm
value in a sample of
452 large USA
industrial
corporations.
The study presents evidence
that small boards of directors
are more effective and those
companies tend to achieve a
higher market value
There is no
conclusive evidence
that small boards are
more effective.
The study is to evaluate
the effect of all CG
mechanisms on firm
performance (COC).
74
Hermalin and
Weisbach (1996)
To evaluate the effects
of board composition
and effects of direct
incentives to firm
performance
The independent
variable was the
board composition
while the dependent
variable was the
firm’s value as
measured by Tobin’s
Q and accounting
measures
The study found no relation
between the proportion of
outside directors and firm
performance Similarly she
found no relation between
firm performance and the
proportion of outsiders on
committees focused on
monitoring
The study only used
Tobin’s Q as the sole
measure of firm
performance
It also relied on
market equity values
that may be
overstated
In the study, I intend to
construct the CGI as per
Black et at (2006) which
will incorporate eight
CG variables. Firm
performance is to be
measured using COC.
Shleifer and Visny
(1997)
To examine the
relation between
ownership
concentration and the
firm’s value.
The independent
variable was the
ownership
concentration while
the dependent
variable was the
firm’s value as
measured by share
market prices
The study found that an
increase in ownership
concentration would be
associated with an increase in
the firm’s value.
The levels of ownership
concentration is US and UK
are low compared to other
countries
The study does not
provide conclusive
evidence, but they do
highlight that policy
conclusion of the
results based in US
and UK data are not
necessarily
transferable to other
countries.
The study is to evaluate
the effect of all CG
mechanisms on firm
performance by using
COC
Gompers, Ishii,
&Metrick, (2003).
To investigate the
effect of CG on the
stock returns among
1500 large firms in
USA between 1990
G Index (24 CG
variables) compiled
from IRRC and stock
returns
Q’it= at + btXit+
CG is strongly correlated with
stock returns during the
1990s in the US. The results
clearly support the hypothesis
that well-governed companies
The study used quite
a number of CG
variables and studies
by BCF found out
that only six variables
Will incorporate only
eight CG variables in
the construction of the
CGI. Will also use the
accounting based
75
and 1999 ctWit+ eit, have higher equity returns. really matter. measures and other
measures like COC and
market based measures.
Ashbaugh et at
(2004)
To investigate the
effect of CG on the
COE
Financial information
quality, ownership
structure,
shareholders rights
and board structure
Firms with better CG enjoyed
reduction in COE. All four
CG variables significantly
influenced the COE reduction
The study only
looked at COEC as
the performance
measure.
The study will
investigate the overall
COC i.e the WACC
which includes both the
COE and COD
Huang, (2004) To investigate the
effect of firm-level
shareholder rights on
the COE
G Score as compiled
by Gompers, et
al.,(2003)
The weak shareholder rights
resulted in higher COEC, and
change in CG score positively
and significantly associated
with the change in COEC
The study only
looked at COE as the
performance measure
and only considered
the effects of firm-
level shareholders
rights
The study will look at
the G Score as complied
by Black et al (2006)
and also consider the
overall COC
Brown
&Caylor,(2006)
To test the significance
of CG metrics and firm
performance as
measured by Tobin’s
Q Using ISS data for
2,327 firms
CG metrics (51
governance metrics)
and firm performance
as measured by
Tobin’s Q.
The authors identified five
governance provisions that
are linked to firm value.
The authors only
used Tobin’s Q as a
metric for firm
performance.
The study is to evaluate
the effect of all CG
mechanisms on firm
performance by using
COC.
Black, et al. (2006) To determine the effect
of CG on a firms
market value among
Independent variable
was the CGI and the
dependent variables
Firms with high market
values may adopt good
governance practices, may
The study that
omitted economic
variables which
Other forms of
performance
measurements will be
76
515 Korean companies
based on 2001 Korean
Stock Exchange
were Tobin's Q&
ROA.
endogenously choose
different governance
practices, and may adopt
good governance rules.
predict both
governance and share
prices.
used i.e. the ROA,
Tobin’s Q and COC.
Piot and Missonier-
Piera,(2007)
To investigate the
impact of firm-level
CG on COD
Ratio of outside
directors,
compensation and
audit committee
All the three CG variables
have a significantly reducing
effect on the COD
The study only
looked at COD as the
performance
measure.
The study will
investigate the overall
COC i.e. the WACC
which includes both the
COE and COD
Bebchuk et al
,(2009)
To identify provisions
that contribute to the
negative correlation
with Tobin’s Q based
on GIM (2003)
Used Tobin’s Q as
measure of firm value
TQ = MV of
assets/BV of assets.
Independent
variables: standard
financial controls.
Bebchuk et al. attributed the
largest part of the effects to
the six provisions
Staggered Boards, Limits to
amend by-laws,
Supermajority requirements
for mergers and charter
amendments, Poison pills,
and Golden parachutes
In the study Tobin’s
Q (dependent
variable) was used a
measure of firm
performance.
Other forms of
performance
measurements will be
used i.e. the ROA,
Tobin’s Q and COC.
The study will also
consider eight CG
variables in the
construction of the CGI
77
Aduda and
Musyoka (2011)
To evaluate the
relationship between
executive
compensation and firm
performance in the
Kenyan banking sector
between 2004 and
2008
Multiple regression
models were used to
analyse the data.
Only realized
compensation was
considered. The
board remuneration
was used as a proxy
for executive
remuneration. ROA
and ROE were also
used.
The findings of the study
indicated that accounting
measures of performance are
not key considerations in
determining executive
compensation
Other market based
measures need to be
considered, Other CG
characteristics need
to be included in the
study.
In the study, I intend to
construct the CGI as per
Black et at (2006) which
will incorporate eight
CG variables. Firm
performance is to be
measured using COC.
Ongore V.O and
K’Obonyo(2011)
The effects of
ownership structure on
performance of listed
companies in Kenya
between 2006 and
2008
Investigated the
effects of ownership
structure on firm
performance.
Measures of
performance were
ROA,ROE and DY
The study found out that
ownership structure affects
firms performance
There is a significant negative
relationship between
government ownership and
firm performance
The study only used
the accounting based
performance
measures
The study will not only
consider the ownership
structure, but I will look
CG in EAC
Lishenga (2012) To test the
relationship between
board activity and a
firm's existing CG
CG mechanisms and
firm performance as
measured by Tobin’s
Q, EVA and Cash
Value Added (CVA)
Board activity has a positive
impact on firm value.
Board meeting frequency
increase with declining
performance.
The study only
considered internal
CG mechanisms
The internal and
external CG
mechanisms will be
considered in the CGI.
78
2.8 The Conceptual Framework
The conceptual framework seeks to link CG with firm performance. The agency theory
analyses the internal CG mechanisms while the institutional theory, political theory and
the trade-off theory looks at how the legal, regulatory, leverage and external environment
effect on firm performance. The application of the individual theories in previous
empirical studies has led to mixed evidence. The CGI is constructed based on firm
control mechanisms, the institutional setting, and the impact on performance.
The independent variables in the study are the models of CG variables and they includes
board structure, board composition, the role of the board, board conduct and
performance, board remuneration, disclosure and transparency, internal controls,
accounting to shareholders and corporate ethics.
The dependent variable includes the firm performance as measured by Tobin’s Q, ROA
as well as COC. The COC includes the cost of debt and the cost of equity. COC is used
as an alternative to other measures of firm performance. A firm’s COC reflects investors
required return based on the firm’s risk and a number of possible risks arise when CG is
weak. To measure the COC we obtain the estimated weighted average cost of capital
(WACC) from the security exchanges. CS is considered as the intervening variable and
the main concerns is leverage while RC is considered as the moderating variable between
composite CG and firm performance. Figure 2.1 shows the conceptual model.
79
Figure 2.1: Conceptual Model
2.9 Research Hypotheses
The study will seek to test the following hypotheses:
H1: There is no significant relationship between corporate governance and firm
performance among the listed companies at the East African community securities
exchanges.
Source: Author 2014
H2
H1
H3
REGULATORY
COMPLIANCE
• Shareholders rights
• Minority shareholders
• Creditors’ rights
• Accounting standards
H4 MODERATING VARIABLE
CAPITAL
STRUCTURE
• Firm Leverage
INTERVENING VARIABLE
H5
H6
CORPORATE
GOVERNANCE
• Board structure and composition
• Ownership and Shareholding
• Transparency, Disclosures and
Auditing
• Board remuneration
• Corporate ethics
INDEPENDENT VARIABLE
FIRM
PERFORMANCE
• Cost of capital
• Tobin’s Q
• Return on
assets
DEPENDENT VARIABLE
80
H2: There is no significant relationship between corporate governance and capital
structure.
H3: There is no significant relationship between capital structure and firm performance
among the companies listed at the East African community securities exchanges.
H4: There is no significant moderating effect of regulatory compliance on the
relationship between corporate governance and firm performance.
H5: There is no significant intervening effect of capital structure on the relationship
between corporate governance and firm performance
H6: There is no significant joint effect of capital structure and regulatory compliance on
the relationship between corporate governance and firm performance
81
CHAPTER THREE
RESEARCH METHODOLOGY
3.1 Introduction
This chapter discusses the research methodology that guided this study. This includes the
philosophical direction, the research design, the target population, data collection,
operationalization of the study variables, validity and reliability tests, data analysis and
presentation.
3.2 Research Philosophy
Research methods are influenced by philosophical orientations. Developing a
philosophical perspective requires that the researcher makes several core assumptions
concerning two dimensions of research: the sociological dimension and the scientific
dimension. Positivism and phenomenology exist as the two philosophical approaches
forming the foundation of knowledge upon which assumptions and predispositions of a
study are based in other words a subjective (phenomenology/interpretive) approach or an
objective (positivism) approach (Easterby-Smith et al, 1991, Hughes and Sharrock,
1997). These philosophical approaches are defined by assumptions concerning ontology
(reality), epistemology (knowledge), human nature (pre-determined or not) and
methodology (the researcher’s tool-kit). The two main paradigms that guide research in
social sciences are the positivist and phenomenological paradigms.
Positivist paradigm adopts a clear quantitative approach to investigating phenomena
(Smith, 1998). The approach assumes that an objective reality exists which is
82
independent of human behavior and is therefore not a creation of the human mind. The
positivists seek facts or causes of social phenomena with little regard for the subjective
states of individuals. This philosophy believes that universal scientific propositions are
true only if they have been verified by empirical tests. The researcher focuses on facts,
looks for causality and fundamental laws, reduces phenomena to simplest elements,
formulates hypotheses and tests them. This paradigm involves operationalizing concepts
so that they can be measured, and taking large samples (Saunders, Lewis, and Thornhill,
2007).
Phenomenological paradigm focuses on the immediate experience and description of
things as they are, not what the researcher thinks they are. This approach involves
gathering large amounts of rich information based on belief in the value of understanding
the experiences and situations of a relatively small number of subjects (Veal, 2005). This
paradigm believes that rich insights into this complex world are lost if such complexity is
reduced to a series of law-like generalizations. There is need to discover the details of the
situation to understand the reality. It is necessary to explore the subjective meanings
motivating people’s actions in order to be able to understand these (Cooper and
Schindler, 2008). This approach assumes that reality is multiple, subjective and mentally
constructed by individuals. The use of flexible and multiple methods is desirable as a way
of studying a small sample in depth over time that can establish warranted assert ability
as opposed to absolute truth. The researcher interacts with those being researched, and
findings are the outcome of this interactive process with a focus on meaning and
understanding the situation or phenomenon under examination (Crossan, 2003).
83
This study was inclined to a positivist research philosophy because it was based on
existing body of knowledge, the researcher reviewed literature from previous related
studies, a conceptual framework was developed, and scientific processes were followed
in hypothesizing fundamental laws from which observations were deduced so as to
determine the truth or falsify the stated hypotheses. The study verified propositions
through empirical tests. The positivist approach also relies on taking large samples hence
the researcher studied the entire population so as to generalize the findings. An essential
step in conducting social science research is to determine and justify the chosen research
philosophy adopted by the researcher. Inter-related paradigmatic assumptions regarding
the nature of reality, the researcher's role and the research process trigger scientific
research. Research philosophy has two paradigms, these are positivistic and the
interpretative paradigms (Hussey and Hussey, 1997; Patton 1990). These paradigms
represent the end of a continuum in social science research, which illustrates the links
between these ontological, epistemological and methodological assumptions.
3.3 Research Design
Research design is the blueprint used to guide a research study to ensure that it addresses
the research problem. There are three broad types of research design, that is: exploratory
research design; descriptive research design; and causal research design. The research
design that was used is descriptive cross-sectional design. A descriptive study involves
description of phenomena or characteristics associated with a subject population (the
who, what, when, where, and how of a topic). It allows estimates of the proportions of a
84
population that has these characteristics. Discovery of associations among different
variables is possible, in order to determine if the variables are independent (or unrelated)
and if they are not, then to determine the strength or magnitude of the relationship. Cross-
sectional studies are carried out once and represent a snapshot at one point in time
(Cooper and Schindler, 2008).
The study seeks to explain the relative influence of CGI on firm performance. The study
therefore employed a descriptive cross-section research design, which involves the
collection of data to assess the hypothesized relationship among variables. Descriptive
design helps to answer questions concerning the current status of the subjects under study
(Mugenda and Mugenda, 2003) while cross-sectional survey means that elements are
measured at a single point in time and that the study made use of the entire population as
opposed to a sample. A cross-sectional descriptive survey was used to describe
characteristics or features and to analyze their frequency, their distribution and
observable phenomena. Nachmias and Nachmias (2004) contend that cross sectional
studies help a researcher to establish whether significant associations among variables
exist at some point in time.
A descriptive cross-sectional design enabled the researcher to discover any relationship
between corporate governance, capital structure, regulatory compliance and firm
performance of companies listed at East African securities exchange. The design was
also chosen considering the type of data and the analysis that was carried out. Aduda and
85
Musyoka (2011) used a similar research design, where they investigated the relationship
between executive compensation and firm performance of the Kenyan banks.
3.4 Target Population and Sampling
The target population for this study comprised all the listed companies at the East African
Securities Exchange. There were a total of ninety eight (98) companies listed at the East
African Securities Exchange as at 31st December 2013 as shown in appendix IV(61
companies listed NSE, 16 in DSE, 16 in USE and 5 in RSE). The intention was to include
all the 98 listed companies in the study but only 56 firms were finally included in the
analysis, because not all the companies had full financial reports for the study period. The
study only considered firms which had been listed and had full financial statements from
2009 to 2013. The list of quoted companies has been obtained from NSE, DSE, USE,
RSE and CMA websites.
The quoted companies are preferred as they have a defined structure, a legal mandate to
operate and are likely to exhibit elaborate relationships between study variables. The
population was divided into various strata, i.e. as per the security exchanges. The details
are shown in Appendix III.
3.5 Data Collection
The study used secondary data which was obtained through a review of financial
statements where an index was constructed both for corporate governance and regulatory
compliance. For firm performance the financial statements were reviewed to get Return
86
on Assets (ROA), Tobin Q and Cost of Capital (COC). Capital structure data for
calculating leverage was gotten from the same financial statements. The period of study
was 2009, 2010, 2011, 2012 and 2013. This period is significant because it signifies when
the RSE first listed companies.
A standardized structured CGI index was used and the questions were constructed using
information obtained from the best code of practice of CG from the regulatory authorities
in the EAC exchanges. The CGI (See Appendix II) was constructed as a proxy for
governance and it is based on 56 binary objective survey questions obtained from
secondary data. CGI has a value of between 0 and 100, and it is expected that poorly
governed firms will have lower scores, while better governed companies will have higher
scores (Brown and Caylor, 2004)
A structured regulatory compliance index (RCI) was used and the questions were
constructed using information obtained from the best code of practice of CG from the
regulatory authorities in the EAC exchanges. The RCI (See Appendix I) was constructed
as a proxy for regulatory compliance of the listed companies and it is based on 35 binary
objective survey questions obtained from secondary data. A similar index was used by La
Portal, et al. (2002).
3.6 Operationalization of Variables
The study has four variables of interest. The independent variable is the composite CG
measured by the CGI. The dependent variable is the firm performance as measured by
87
Tobin Q, ROA and COC while capital structure is the intervening variable and rules and
regulations is the moderating variable.
The independent variable CG was measured by the CGI as per Black et al (2006). The
CGI is divided into eight sub-indices consisting of the governance characteristics. The
capital structure is measured by firm leverage and liquidity while rules and regulations is
measure by the code of CG questionnaire. The dependent variable firm performance is
measured by ROA, Tobin Q and COC (See table 3.2 below)
Table 3.2: Summary of Research Variables
Variables Indicators Measure
CORPORATE GOVERNANCE INDEX(INDEPENDENT VARIABLE)
Composite Corporate
Governance(CG Index)
Board structure and
composition
CGI sub index A
Ownership and shareholding CGI sub index B
Transparency, disclosures and
auditing
CGI sub index C
Board remuneration CGI sub index D
Corporate ethics CGI sub index E
CAPITAL STRUCTURE
Leverage
• Total liabilities to total assets
(capital structure)-Financial
leverage
• Total debt (Total book value of debt)
divided by total capital (market value
of equity + book value of debt).
FIRM PERFORMANCE (DEPENDENT VARIABLE)
88
Return on Assets
(ROA)
Ratio of operating income and
total assets
Measures how profitable a company is
relative to its total assets
ROA=Net Income/Total Assets
Tobin’s Q Ratio of market value to book
value of assets. Market value of
assets is computed as market
value of equity plus book value
of assets minus book value of
equity
Use of book values of total assets and
total equity:
Q=Market capitalization+(Total
assets-equity)/Total assts.
Natural log is used in most
specifications
Cost of Capital(COC) Weighted average cost of
capital(WACC)
The weighted average cost of capital is
calculated as:WACC= (D/ (D+E) x
(1-T) x Kd) + (E/(D+E) x Ke)
Cost of Equity (COE) Investors required return based
on the firm’s risk
OJ Model
COE(Ke)=A+√{A 2+e1/Po[g2-g1]}
Cost of Debt (COD) Interest on firm’s debt Interest expense for the financial year
divided by the average financial debt
during the same year
REGULATORY COMPLIANCE
Regulatory
Compliance Index
Shareholders rights,
Minority shareholders rights,
Creditors’ rights
Accounting standards
disclosure
Regulatory Compliance Index (RCI)
Source: Researcher (2014)
89
3.7 Reliability and Validity Considerations
Reliability of a measure has two parts- its stability over time and the consistency of the
instrument in measuring the concept. The reliability of the instruments was evaluated
through Cronbach’s alpha which measures the internal consistency and used to describe
the reliability of factors extracted from questionnaires and the higher value indicates a
more general scale (Cooper and Schindler, 2008).
Validity is the extent to which the instrument measures what it purports to measure. CG
is multi-dimensional concept measured using CGI which combines eight variables which
are converted into binary variables and due to binary requirement the composite measure
is limited in capturing the variation and to control for validity the study introduces the
scaling method. The overall composite variable is used to eliminate the effect of CG
missing data.
3.8 Data Analysis
The data obtained on the CG, capital structure, and regulatory compliance was analyzed
using descriptive statistics (mean, standard deviation, skewness and kurtosis). Regression
analysis (simple regression analysis, multiple regression analysis and stepwise regression
analysis) and Pearson’s Product Moment Correlation analysis were used to establish the
nature and magnitude of the relationships between the variables of the study and to test
the hypothesized relationships (See Table 3.3). Descriptive statistics such as frequencies
and percentages were computed for organizational data and multiple choice questions in
order to describe the main characteristics of the variables of interest in the study. Mean
90
scores were computed for binary type of questions. Data was presented in form of tables.
Pearson’s correlation analysis will used to measure the degree of linear relationship
between the variables of the study. To investigate the interactions between variables,
regression analysis and multiple regression analysis will be used.
Table 3.3: Summary of Research Objectives, Hypotheses, Analytical Methods, Statistical
test and Interpretation
Objectives Hypotheses Analytical methods Interpretation
To examine the effect
of CG on firm
performance among the
listed companies in
East African
Community Securities
Exchange.
Hypothesis 1 There
is no significant
relationship between
CG and firm
performance among
the listed companies
at the EACSE.
Simple Linear Regression Analysis
Firm Performance = f (CG)
Y = β0 +β1X1 +ε
Y= Firm Performance, β0=
intercept,X1=CGI,β1=coefficient,
ε=Error term
Relationship
exists if ββββ1
Significant
To evaluate the effect
of corporate
governance on capital
structure among
companies listed at the
East African
Community Securities
Exchange.
Hypothesis 2 There
is no significant
relationship between
CG and capital
structure.
Simple Linear Regression Analysis
Capital Structure = f (CG)
Y = β0 +β1X1 +ε
Y= Capital Structure, β0=
intercept,X1=CGI,β1=coefficient,
ε=Error term
Relationship
exists if ββββ1 is
significant.
91
To determine the effect
of capital structure on
firm performance
among the listed
companies in the East
African Community
Securities Exchange.
Hypothesis 3 There
is no significant
relationship between
capital structure and
firm performance
among the
companies listed at
the EACSE.
Simple Linear Regression Analysis
Firm Performance = f (Capital
Structure)
Y = β0 +β1X1 +ε
Y= Firm Performance, β0=
intercept,X1=Capital
Structure,β1=coefficient, ε=Error
Relationship
exists if ββββ1
Significant
oefficie
To establish the
moderating effect of
regulatory compliance
on the relationship
between CG and firm
performance among the
companies listed at the
EACSE.
Hypothesis 4:
There is no
significant effect of
rules and regulations
on the relationship
between CG and
firm performance
Multiple Linear Regression
Analysis
Firm performance = f (CG,
Regulatory compliance)
Y = β0 +β1X1+β2X2+ε
Y= Firm performance, β0=
intercept, X1= CGI, X2=
Regulatory compliance, β1, β2=
coefficients, ε= Error
Relationship
exists if at least
of the ββββ1...ββββ2 is
significant.
To determine the
intervening effect of
capital structure on the
relationship between
corporate governance
and firm performance
among the companies
Hypothesis 5:
There is no
significant
intervening effect of
capital structure on
the relationship
between corporate
Multiple Linear Regression
Analysis
Firm performance = f (CG, Capital
Structure)
Y = β0 +β1X1+β2X2+ε
Y= Firm performance, β0=
intercept, X1= CG, X2= Capital
Relationship
exists if at least
of the ββββ1...ββββ2 are
significant.
92
listed at the EACSE.
governance and firm
performance
Structure, β1, β2= coefficients, ε=
Error
To establish the joint
effect of capital
structure and regulatory
compliance on the
relationship between
corporate governance
and firm performance
among the companies
listed at EACSE
Hypothesis 6:
There is no
significant joint
effect of capital
structure and
regulatory
compliance on the
relationship between
CG and firm
performance
Stepwise Regression Analysis
Firm Performance = f (CG, Capital
Structure, Regulatory Compliance)
Y=β0+β1X1+β2X2+β3X3+ε
Y=Firm Performance,
B0=intercept, X1=CG, X2=Capital
Structure,X3=Regulatory
Compliance, β1, β2, β3, β4=
coefficients, ε= Error term
Relationship
exists if at least
of the ββββ1...ββββ3 are
significant.
3.8.1 Measurement of firm performance
COC was used as an alternative to other measures of firm performance. A firm’s COC
reflects investors required return based on the firm’s risk and a number of possible risks
arise when CG is weak.
Y=β0+β1X1+β2X2+β3X3+ε+εεεε…………………….……………………………………………………………………………………3.1
Y=Firm Performance,
B0=intercept, X1=CG, X2=Capital Structure, X3=Regulatory Compliance, β1, β2, β3,
β4= coefficients, ε= Error term
Where Y and CG are vectors for firm performance and corporate governance respectively
X2=Capital Structure (Total long term debt divided by total assets)
93
To measure the COC we obtain the estimated weighted average cost of capital (WACC)
from the security exchanges. The weighted average cost of capital is calculated as:
COC= (D/(D+E)x (1-T) x Kd) + (E/(D+E) x Ke) ……………………………………………………………………………………………………………………………………………………3.2
Where D/ (D+E) is established using a three-year trailing average of D/E levels. E/
(D+E) is the ratio of the firm’s equity to its capital value. T is the corporate tax rate for
companies. Kd is the cost of debt and Ke is the cost of equity capital.
COE will be calculated using the OJ model as follows:
Ohlson and Juttner-Nauroth (2005 OJ) assumes that price is a function of future earnings,
short-term growth rate, long-term growth rate, and a discount rate. The model is specified
3.2 below
Ke=A+√√√√{A 2+e1/Po[g2-g1]}…………………………………………………………………………………………………………………………………………………………………………………………………………………………………………3.3
Where:Ke = the implied cost of equity capital
A=½[g1+d1/Po] …………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………3.4
Where e1= Earnings per share for year 1
e2= Earnings per share for year 2
g1= Perpetual abnormal earnings growth rate
A= Abnormal earnings
d1=e1multiplied by the dividend payout ratio.
g2=(e2-e1)/e1……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………3.5
To estimate the COE, g1 (perpetual growth rate) mirror the inflation rate and we assume
that the dividend payout remains the same as in year t, that is, DPS t+1= DPS t. Finally, we
require that e2>e1>0 since a negative short-term growth rate is not meaningful in the
setting of abnormal earnings growth model.
94
The COD was calculated by considering the average interest on firm’s debt i.e. the
interest expense for the financial year divided by the average financial debt during the
same year (Piot et al 2007). In order to provide comparisons between the results and
previous studies, the regressions that tested the relation between firm performance and
governance mechanisms were replicated using Tobin’s Q, defined as the market value of
equity plus the book value of debt over total assets as our measure of firm value.
Q= (Market Value of Stock + Book Value of Liabilities)/Book Value of Assets……………………3.6
Market value of stock (common and preferred) will be gotten from market capitalization
at the end of each period. ROA variable is also used as an accounting measure of firm
performance and it is defined as the operating income over total assets.
3.8.2 Corporate Governance Index (CGI)
According to Black et al (2006), the CGI is composed of other sub-indices. In this case
the sub-indices were five namely the board structure and composition (sub-index A),
ownership and shareholding (sub-index B), transparency, disclosure and auditing (sub
index C),board remuneration (sub index D),and corporate ethics(sub index E).The sub-
indices were based on 46 questions.
CGI has a value of between 0 and 100, and that poorly governed firms have lower scores,
while better governed companies have higher scores. In a similar study, Black, et al.
(2006) constructed CGI in their study of 526 companies in the Korean stock exchange
based on six sub-indices. Similarly, Clatcher, et al. (2007), also used the combined code
of corporate governance to construct five sub-indices.
95
CG1 =A+B+C+D+E …………………….…………………….......................………………………………………………………………3.7
Each element in each sub index is constructed to have a value between 0 and 1. To obtain
a sub-index will have totals of 20 and adjusted accordingly. The sub-indices were
regressed individually against the dependent variable.
3.8.3 Relating the Variables
Multiple regression analyses were used to assess the strength of the relationship between
dependent, independent, moderating and intervening variables. Dependent variables
being COC, Tobin Q, and ROA, the independent variables being the determinants of CG
Y= β0+β1X1+β2X2+β3X3+ε…………………….…………………………………………………………………………………3.8
Y=ROA,
B0=intercept, X1=CG, X2=Capital Structure, X3=Regulatory Compliance, β1, β2, β3,
β4= coefficients, ε= Error term
Y= β0+β1X1+β2X2+β3X3+ε…………………….…………………………………………………………………………………3.9
Y=Tobin Q,
B0=intercept, X1=CG, X2=Capital Structure, X3=Regulatory Compliance, β1, β2, β3,
β4= coefficients, ε= Error term
Y= β0+β1X1+β2X2+β3X3+ε…………………….…………………………………………………………………………………3.10
Y=COC,
B0=intercept, X1=CG, X2=Capital Structure, X3=Regulatory Compliance, β1, β2, β3,
β4= coefficients, ε= Error term
96
CHAPTER FOUR
DESCRIPTIVE ANALYSIS AND RESULTS
4.1 Introduction
The chapter presents the outcome of data analysis and findings in line with the objectives
of the Study. The broad objective was to assess corporate governance, capital structure,
regulatory compliance and performance of firms listed at the East African Community
Securities Exchange. The data were analyzed using the Statistical Program for Social
Sciences (SPSS) version 20, by use of both descriptive and inferential statistics.
Descriptive statistics such as minimum, maximum, mean, standard deviation kurtosis and
skewness were used. Tests on the data for the assumptions of linear regression were
conducted and results were within the limits necessary for further statistical tests. The six
hypotheses of the Study were tested using simple and multiple regressions. Correlations
were also conducted between various study variables.
4.2 Tests of Statistical Assumptions
The study performed the tests on statistical assumptions i.e. test of regression assumption
and statistic used. This included test of normality, linearity, independence, and
homogeneity and co linearity. Normality was tested using the Shapiro-Wilk test which
has power to detect departure from normality due to either skewness or kurtosis or both.
Its statistic ranges from zero to one and figures higher than 0.05 indicate the data is
normal (Razali and Wah, 2011). Linearity was tested by use of ANOVA test of linearity
which computes both the linear and nonlinear components of a pair of variables whereby
97
nonlinearity is significant if the F significance value for the nonlinear component is
below 0.05. Independence of error terms, which implies that observations are
independent, was assessed through the Durbin-Watson test whose statistic ranges from
zero to four. Scores between 1.5 and 2.5 indicate independent observations.
Homoscedasticity was tested by use of Levene’s test of homogeneity of variances. If the
Levene statistic is significant at α= 0.05 then the data groups lack equal variances.
Levene’s test measures whether or not the variance between the dependent and
independent variables is the same. Thus it is a check of whether the spread of the scores
(reflected in the variance) in the variables are approximately similar. Multicollinearity
was tested by computing the Variance Inflation Factors (VIF) and its reciprocal, the
tolerance. It is a situation in which the predictor variables in a multiple regression
analysis are themselves highly correlated making it difficult to determine the actual
contribution of respective predictors to the variance in the dependent variable. The
multicollinearity assumption has a VIF threshold value of 10 maximum (Garson, 2012).
Five assumptions of regression were tested and their results together with those of the test
for reliability are summarized in Table 4.4 and Appendix IV. The threshold levels for the
respective test statistics are listed below each assumption. For multicollinearity both the
variance inflation factor (VIF) and its reciprocal (Tolerance) values are listed, the latter in
parentheses. The results showed that the assumptions of regression were met and
subsequently the data were subjected to further statistical analysis including tests of
hypotheses as discussed in the following subsections.
98
Table 4.4: Results of Tests of Statistical Assumptions (Test of regression assumption and statistic used)
N N
orm
ality
(S
hapi
ro-W
ilk
test
)
Line
arity
(A
NO
VA
test
)
Inde
pend
ence
(D
urbi
n-W
atso
n te
st)
Hom
ogen
eity
(L
even
e te
st)
Col
linea
rity
VIF
(T
oler
ance
te
st)
Threshold: Assumption is met if p > 0.05 p > 0.05 1.5- 2.5 p > 0.05 VIF 10 max
Corporate governance
• Board structure and composition
• Ownership and shareholding
• Transparency, disclosure and auditing
• Board remuneration
• Corporate ethics
280 0.39 0.42 2.02 0.64 6.67 (0.15)
Capital structure • Leverage • Liquidity
• Total liabilities to total assets (capital structure)-financial leverage
• Ratio of working capital to total assets
280 0.66 0.37 1.64 4.29 1.12 (0.89)
Regulatory compliance
• Shareholders rights • Minority
shareholders rights • Creditors’ rights • Accounting
standards disclosure
280 0.10 0.16 1.73 0.24 6.10 (0.16)
Firm Performance • Return on
Assets (ROA)
• Tobin’s Q • Cost of
Capital (COC)
• COE • COD
• Ratio of operating income and total assets
• Ratio of market value to book value of assets. Market value of assets is computed as market value of equity plus book value of assets minus book value of equity
• WACC
280 0.10 0.31 2.03 0.80 1.90 (0.60)
99
Normality was tested using the Shapiro-Wilk test which has power to detect departure
from normality due to either skewness or kurtosis or both. The readings of the study were
above 0.05 confirming normality. Normality assumes that the sampling distribution of the
mean is normal. Further Linearity was tested by use of ANOVA test of linearity which
computes both the linear and nonlinear components of a pair of variables whereby
nonlinearity is significant if the F significance value for the nonlinear component is
below 0.05. All the computed readings were above 0.05 confirming linear relationships
(constant slope) between the predictor variables and the dependent variable. The study
further assessed Independence of error terms, which implies that observations are
independent through the Durbin-Watson test whose statistic ranges from zero to four. In
the current study the test results ranged between 1.81 and 2.21 supporting independence
of error terms. Homoscedasticity was tested by use of Levene’s test of homogeneity of
variances. The test was not significant at α= 0.05 confirming homogeneity.
Multicollinearity was tested by computing the Variance Inflation Factors (VIF) and its
reciprocal, the tolerance. It is a situation in which the predictor variables in a multiple
regression analysis are themselves highly correlated making it difficult to determine the
actual contribution of respective predictors to the variance in the dependent variable. The
multicollinearity assumption has a VIF threshold value of 10 maximum (Gatwirth et al.,
2009). In the current study tolerance ranged from 0.60 to 0.80 and therefore its reciprocal,
the VIF was between one and two, way below the threshold.
100
4.3 Descriptive Statistics
Descriptive measures involved mean, maximum, minimum, standard error of estimate,
skewness and kurtosis. Mean is a measure of central tendency used to describe the most
typical value in a set of values. The standard error is a statistical term that measures the
accuracy within a set of values. Skewness is a measure of symmetry, or more precisely,
the lack of symmetry. A distribution, or data set, is symmetric if it looks the same to the
left and right of the center point. Kurtosis is a measure of whether the data are peaked or
flat relative to a normal distribution (Cooper and Schindler 2008).
The study determined the measures of corporate governance which included board
structure and composition, board role and responsibilities, board conduct and
performance, board remuneration, disclosure and transparency, risk, internal control,
Audit and compliance, accountability and assurance to shareholders and corporate ethics
among the firms listed at the East African Community Securities Exchange. The pertinent
results are presented in Table 4.5
101
Table 4.5: Descriptive statistics results of the main variables included in the model
N
Mea
n
Std
.
Dev
iatio
n
Ske
wne
ss
Std
. E
rror
of
Kur
tosi
s
Std
. E
rror
of
Min
imum
Max
imum
Valid
Leverage 280 0.294364 0.242611 2.055 0.146 6.813 0.29 0.001 1.6845
Return on
Assets
280 0.205132 0.167727 0.487 0.146 0.482 0.29 -0.4404 0.6018
Tobin's Q 280 1.334533 0.768506 1.899 0.146 4.072 0.29 0.1255 4.7723
Cost of
capital
280 0.050914 0.042809 1.855 0.146 5.637 0.29 0.002 0.3218
Corporate
Governance
index
280 0.72684 0.104942 0.124 0.146 -1.27 0.29 0.54 0.9
Regulatory
Compliance
Index
280 0.5566 0.09691 0.108 0.146 -1.368 0.29 0.4 0.7
The results showed that leverage had a mean of 0.2943 with a minimum of 0.001, a
maximum of 1.6845, skewness 2.055 and kurtosis of +6.813. Comparatively, Return on
Assets had a mean of 0.2051, minimum of -0.4404, maximum of 0.6018, skewness of
0.487 and kurtosis of +0.482. Tobin’s Q had a mean of 1.334, minimum of 0.1255,
maximum of 4.7723, skewness of 1.899 and kurtosis of +4.072. Corporate governance
102
index had a mean of 0.7268, minimum of 0.54, maximum of 0.90, skewness of 0.124 and
kurtosis of -1.27.
Analysis of skewness shows that leverage, Return on Assets, Tobin's Q, Cost of capital,
Corporate Governance index and Liquidity are asymmetrical to the right around its mean,
therefore it means that most of the firms are doing well when the above measures are
considered. Regulatory compliance index is asymmetrical to the left around its mean,
which means that most of the index score were less than the mean in the four of the EAC
countries and additionally, leverage is highly peaked compared to other regressors.
4.3.1 Corporate governance
The study determined the corporate governance among the companies listed at the East
Africa Communities Securities Exchange among the East African countries i.e. Kenya
(NSE), Tanzania (DSE), Uganda (USE) and Rwanda (RSE). The constructs of corporate
governance determined comparatively are Board structure and composition, ownership
and shareholding, board role and responsibilities, board remuneration, disclosure and
transparency and corporate ethics. The comparative results of the four countries are as
indicated in Tables 4.6 to Table 4.28
103
Table 4.6: Board Structure and Composition (KENYA-NSE)
N
Mea
n
Max
imu
m
Min
imu
m
Std
. D
ev.
Ske
wn
ess
Ku
rto
sis
Jar
qu
e-B
era
Pro
bab
ility
Board size 43 0.534 0.887 0.231 0.7247 0.049 2.034 4.581 0.0995
Role and functions of
board is stated
43 0.899 0.921 0.321 0.3318 0.829 3.225 13.311 0.0012
Chairman and CEO
separation
43 0.743 0.832 0.442 0. 342 0.997 3.567 20.416 0.0037
Information about
independent directors
43 0.919 0.984 0.832 0.238 0.698 2.314 11.488 0.0032
Board meeting
attendance
43 0.834 0.986 0.322 0.4241 0.038 3.131 3.482 0.0884
Outside directors
attendance in meetings
43 0.788 0.822 0.211 0.2311 0.629 2.224 9.322 0.0042
Existence of the position
of CFO
43 0.842 0.931 0.541 0. 442 0.897 3.461 13.413 0.0021
Directors representing
minority shareholders
43 0.811 0.932 0.733 0.4321 0.793 3.312 11.435 0.0013
Biography of the board
members
43 0.835 0.983 0.532 0.625 0.043 3.031 4.567 0.098
Changes is the board
structure is indicated
43 0.893 0.924 0.622 0.4316 0.629 3.214 9.313 0.016
Average score 43 0.8098
0.9202
0.4787
0.4298
0.5602
2.9513
10.1328
0.03176
104
The results in Table 4.6 reveal that mean score for the ten statements used to measure
board structure and composition was 0.8098. The overall mean score of 0.534 (moderate)
shows that the firms under NSE have board size is between 6-9. In addition, the results
show that the 61 NSE firms surveyed have roles and functions of board stated (mean
score=.899, SD=.3318). Chairman and CEO separation (mean score=.743, SD=.342),
Information about independent directors (mean score=.919, SD=.238) and that Board
meeting attendance (mean score=.834, SD= .4241). Outside directors attendance in
meetings (mean score=.788, SD= .2311), Existence of the position of CFO (mean
score=.842, SD= .442), Directors representing minority shareholders (mean score=.811,
SD= .4321), Biography of the board members (mean score=.833, SD= .625) and Changes
is the board structure (mean score=.893, SD= .4316) is indicated. From skewness, the
study observed that the average score of board structure and composition constructs are
positively skewed (0.5602) and is very near to zero which clarified that the constructs are
asymmetrical. Kurtosis values indicated that all the sub constructs have platy-kurtic
distribution and it is concluded that they are normally distributed (2.9513).
Board structure and composition plays a major role in CG especially board size and
independence. The introduction of independent directors is an important arrangement in
monitoring the effectiveness of BOD. It is therefore imperative to improve effectiveness
of independent directors in monitoring managers especially to strengthen their
independence. Regarding the board size, descriptive statistics only 53.4% of firms
maintain board size of between 6 and 9 board members. The mean of chairman and CEO
separation was 74.3 % which means that majority of the companies have a clearly
105
accepted division of responsibilities at the head of the company, which will ensure a
balance of power and authority, such that no one individual has unfettered powers of
decision. Shleifer and Vishny (1998) revealed that monitoring role of a company is
actually performed by large shareholders. Large shareholders are entitled to receive
significant cash flows from the company to cover the cost of monitoring and information
gathering. Lipton and Lorsh (1992) augured that large borders are less effective and
becomes less effective to manage.
Companies are normally keen on increasing improving their performance by
continuously putting in place a balance board with NED and also have frequent and
effective board meetings. Firms can increase their performance by having on well
diversified board with experience. Hermalin and Weisbach (2001) noted that firms with
more independent directors achieved improved profitability. Lipton and Lorsch (1992)
and Vafeas (1999) also noted that board meetings are important in improving
performance. The findings of the study are in line with existing literature which posits
that board structure and composition effects firm performance
106
Table 4.7: Board Structure and Composition (TANZANIA-DSE)
N M
ean
Max
imu
m
Min
imu
m
Std
. D
ev.
Ske
wn
ess
Ku
rto
sis
Jar
qu
e-B
era
Pro
bab
ility
Board size is between
6-9
5 0.813 0.976 0.332 0.2241 0.595 3.044 11.492 0.0094
Role and functions of
board is stated
5 0.844 0.953 0.422 0.4311 0.723 3.441 10.322 0.0041
Chairman and CEO
separation
5 0.842 0.931 0.543 0. 441 0.692 3.335 14.527 0.0042
Information about
independent directors
5 0.925 0.971 0.621 0.3343 0.675 2.411 10.476 0.0041
Board meeting
attendance
5 0.878 0.938 0.432 0.4324 0.385 2.133 12.456 0.0082
Outside directors
attendance in
meetings
5 0.793 0.889 0.645 0.4541 0.525 2.234 11.341 0.0031
Existence of the
position of CFO
5 0.879 0.958 0.432 0. 442 0.693 3.532 12.414 0.0022
Directors
representing minority
shareholders
5 0.876 0.978 0.634 0.2323 0.569 3.423 10.541 0.0035
Biography of the
board members
5 0.848 0.963 0.523 0.522 0.545 3.241 9.641 0.058
Changes is the board
structure is indicated
5 0.994 0.997 0.543 0.3314 0.631 3.243 9.323 0.023
Average score 5 0.8692
0.9554
0.5127
0.3702
0.603
3.0037
11.253
0.0119
The results in Table 4.7 yield an overall mean score of .8692. The overall mean score of
.813 shows that the firms under DSE have board size is between 6-9. In addition, the
results show that the DSE firms surveyed have roles and functions of board stated (mean
score=.844, SD=.4311). Chairman and CEO separation (mean score=.842, SD=.441),
107
Information about independent directors (mean score=.925, SD=.3343) and that Board
meeting attendance (mean score=.878, SD=.4324). Outside directors attendance in
meetings (mean score=.793, SD= .4541), Existence of the position of CFO (mean
score=.879, SD= .432), Directors representing minority shareholders (mean score=.876,
SD= .634), Biography of the board members (mean score=.848, SD= .543) and Changes
is the board structure (mean score=.994, SD= .543) is indicated. From skewness, the
study observed that the average score of board structure and composition constructs are
positively skewed (.6033) and is very near to zero which clarified that the constructs are
asymmetrical. Kurtosis values indicated that all the sub constructs have platy-kurtic
distribution and it is concluded that they are normally distributed (3.0037).
Board structure and composition constitutes board size, board independence and board
meeting. The introduction of independent directors is an important arrangement in
monitoring the effectiveness of BOD and it has a score of 92.5%. It is therefore
imperative to improve effectiveness of independent directors in monitoring managers
especially to strengthen their independence. Regarding the board size, descriptive
statistics only 81.3% of firms maintain board size of between 6 and 9 board members.
The mean of chairman and CEO separation was 84.2 % which means that majority of the
companies have a clearly accepted division of responsibilities at the head of the company,
which will ensure a balance of power and authority, such that no one individual has
unfettered powers of decision.
108
Table 4.8: Board Structure and Composition (UGANDA-USE)
N M
ean
Max
imum
Min
imum
Std
. Dev
.
Ske
wne
ss
Kur
tosi
s
Jar
que-
Ber
a
Pro
babi
lity
Board size is
between 6-9
6 0.912 0.978 0.632 0.3243 0.592 2.342 10.456 0.0031
Role and functions
of board is stated
6 0.955 0.992 0.621 0.3516 0.556 2.731 7.311 0.0032
Chairman and CEO
separation
6 0.741 0.832 0.642 0. 342 0.482 2.325 4.527 0.0031
Information about
independent
directors
6 0.823 0.961 0.522 0.3441 0.573 2.313 8.476 0.0030
Board meeting
attendance
6 0.774 0.818 0.512 0.5322 0.486 -2.113 8.456 0.0071
Outside directors
attendance in
meetings
6 0.743 0.823 0.542 0.3532 0.534 2.534 9.341 0.0020
Existence of the
position of CFO
6 0.772 0.845 0.531 0. 464 0.571 -3.534 10.414 0.0041
Directors
representing
minority
shareholders
6 0.774 0.865 0.532 0.2356 0.467 3.521 8.541 0.0023
Biography of the
board members
6 0.843 0.954 0.531 0.225 0.565 3.342 11.641 0.046
Changes is the
board structure is
indicated
6 0.945 0.978 0.512 0.2315 0.731 3.254 13.323 0.032
Average score 6 0.828
0.904
0.558
0.325
0.556
1.026
9.248
0.0105
109
The results in Table 4.8 yield an overall mean score of .8282. The overall mean score of
.912 shows that the firms under USE have board size is between 6-9. In addition, the
results show that the USE firms surveyed have roles and functions of board stated (mean
score=.955, SD=.3516). Chairman and CEO separation (mean score=.741, SD=.342),
Information about independent directors (mean score=.823, SD=.3441) and that Board
meeting attendance (mean score=.774, SD=.5322). Outside directors attendance in
meetings (mean score=.743, SD= .3532), Existence of the position of CFO (mean
score=.772, SD= .464), Directors representing minority shareholders (mean score=.774,
SD= .2356), Biography of the board members (mean score=.843, SD= .225) and Changes
is the board structure (mean score=.945, SD= .2315) is indicated. From skewness, the
study observed that the average score of board structure and composition constructs are
positively skewed (.5557) and is very near to zero which clarified that the constructs are
asymmetrical. Kurtosis values indicated that all the sub constructs have platy-kurtic
distribution and it is concluded that they are normally distributed (1.0207).
Board structure and composition score for companies quoted at DSE gives a higher mean
score of 82.8%. The changes in the board structure have a score of 94.5%, which means
the companies are transparent about the changes that take place therefore CG is
enhanced.
110
Table 4.9: Board Structure and Composition (RWANDA-RSE)
N M
ean
Max
imum
Min
imum
Std
. Dev
.
Ske
wne
ss
Kur
tosi
s
Jar
que-
Ber
a
Pro
babi
lit
y
Board size is
between 6-9
2 0.735 0.843 0.333 0.2243 0.442 3.042 4.581 0.0292
Role and
functions of board
is stated
2 0.692 0.725 0.421 0.2318 0.522 3.113 5.311 0.0024
Chairman and
CEO separation
2 0.641 0.738 0.541 0. 242 0.692 3.421 9.416 0.0047
Information about
independent
directors
2 0.713 0.834 0.532 0.138 0.591 3.314 6.488 0.0042
Board meeting
attendance
2 0.733 0.885 0.422 0.2242 0.034 4.131 4.482 0.0784
Outside directors
attendance in
meetings
2 0.682 0.723 0.512 0.1312 0.521 4.224 7.322 0.0052
Existence of the
position of CFO
2 0.541 0.711 0.341 0. 342 0.495 4.461 9.413 0.0031
Directors
representing
minorities
2 0.712 0.833 0.433 0.3322 0.594 5.312 8.435 0.0023
Biography of the
board members
2 0.734 0.853 0.432 0.2251 0.042 3.031 5.567 0.048
Changes is the
board structure is
indicated
2 0.792 0.823 0.422 0.4511 0.645 2.214 7.313 0.026
Average score 2 0.6975 0.7968 0.4389 0.24473 0.451 3.626 6.8328 0.0203
111
The results in Table 4.9 yield an overall mean score of .6975. The overall mean score of
.735 shows that the firms under RSE have board size is between 6-9. In addition, the
results show that the RSE firms surveyed have roles and functions of board stated (mean
score=.692, SD=.2243). Chairman and CEO separation (mean score=.641, SD=.242),
Information about independent directors (mean score=.713, SD=.138) and that Board
meeting attendance (mean score=.733, SD=.2242). Outside directors attendance in
meetings (mean score=.682, SD= .1312), Existence of the position of CFO (mean
score=.541, SD= .342), Directors representing minority shareholders (mean score=.712,
SD= .3322), Biography of the board members (mean score=.734, SD= .2251) and
Changes is the board structure (mean score=.792, SD= .4511) is indicated. From
skewness, the study observed that the average score of board structure and composition
constructs are positively skewed (.451) and is very near to zero which clarified that the
constructs are asymmetrical. Kurtosis values indicated that all the sub constructs have
platy-kurtic distribution and it is concluded that they are normally distributed (3.6263)
Board structure and composition score for companies quoted at RSE gives a higher mean
score of 69.75%. The mean score in RSE is lower than the score of other securities
exchanges in East African Community countries, this attributed to the fact the exchange
established only five years ago.
112
Table 4.10: Ownership and Shareholding (KENYA-NSE)
N M
ean
Max
imu
m
Min
imu
m
Std
. D
ev.
Ske
wn
ess
Ku
rto
sis
Jar
qu
e-
Ber
a
Pro
bab
ility
Presence of outside
blockholders (more
than 10%)
43 0.834 0.987 0.331 0.4247 0.245 2.124 3.581 0.0895
The CEO own shares 43 0.989 0.921 0.321 0.3318 0.829 3.225 13.311 0.0012
Directors ownership
other than the CEO
and Chairman
43 0.743 0.832 0.542 0. 442 0.897 3.467 16.416 0.0047
Chairman or CEO is
block holder (10%)
43 0.719 0.884 0.732 0.338 0.498 2.314 10.488 0.0034
Concentration of
ownership (top five)
43 0.735 0.886 0.422 0.3241 0.028 3.231 3.582 0.0784
Dividend policy 43 0.688 0.722 0.311 0.3311 0.729 3.224 8.322 0.0032
Disclosure of staff
benefits other than
wages and salaries
43 0.743 0.832 0.643 0. 543 0.799 2.471 9.413 0.0031
Disclosure of CS
report
43 0.712 0.832 0.873 0.5322 0.693 3.312 8.435 0.0013
Average score
43 0.7703 0.862 0.521 0.380 0.589 2.921 9.193 0.0231
The results in Table 4.10 show that the averages mean scores for the ownership and
shareholding for the firms under NSE is 0.7703. Presence of outside block holders (more
than 10%) had an overall mean score of 0.834 and SD =0.4247. In addition, the results
113
show that the NSE firms surveyed the CEO own shares (mean score=.989, SD=.3318).
Directors ownership (block ownership) other than the CEO and Chairman (mean
score=.743, SD=.442), Chairman or CEO is block holder (10%) (mean score=.719,
SD=.338) and Concentration of ownership (top five) (mean score=.735, SD=.3241).
Dividend policy (mean score=.688, SD= .3311), Disclosure of staff benefits other than
wages and salaries (mean score=.743, SD= .543), Disclosure of company secretary in
annual report with description of duties and roles (mean score=.712, SD= .5332). From
skewness, the study observed that the average score of ownership and shareholding are
positively skewed (.589) and is very near to zero which clarified that the constructs are
asymmetrical. Kurtosis values indicated that all the sub constructs have platy-kurtic
distribution and it is concluded that they are normally distributed (3.312).
Ownership and shareholding includes presence of outside block holders owning more
than 10% of shareholding, CEO owning shares, directors ownership, chairman or CEO
are block holders, concentration of ownership, disclosure of staff remuneration and
disclosure of the company’s annual report. The index score for companies listed at NSE
was 77.03% which was high. Investors with large ownership stakes have strong incentive
to maximize their firms’ value and are able to collect information and to oversee
managers, and this can help overcome the principal-agent problem (Sheilfer and Vishny,
1997). The findings of the study are in line with existing literature which posits that
ownership and shareholding concentration effects firm performance
114
Table 4.11: Ownership and Shareholding (TANZANIA-DSE)
N M
ean
Max
imum
Min
imum
Std
. Dev
.
Ske
wne
ss
Kur
tosi
s
Jar
que-
Ber
a
Pro
babi
lity
Presence of outside
blockholders (more
than 10%)
5 0.613 0.876 0.432 0.1241 0.495 2.044 9.492 0.0034
The CEO own
shares
5 0.744 0.853 0.422 0.3311 0.623 2.441 7.322 0.0021
Directors ownership
(block ownership)
other than the CEO
and Chairman
5 0.542 0.831 0.443 0. 341 0.592 2.335 5.527 0.0032
Chairman or CEO is
block holder (10%)
5 0.625 0.871 0.421 0.234 0.575 1.411 5.476 0.0031
Concentration of
ownership (top five)
5 0.678 0.838 0.332 0.3324 0.585 1.133 6.456 0.0072
Dividend policy 5 0.593 0.789 0.545 0.3541 0.425 1.234 5.341 0.0021
Disclosure of staff
benefits other than
wages and salaries
5 0.679 0.858 0.332 0. 342 0.593 1.532 5.414 0.0012
Disclosure of
company secretary
in annual report with
description of duties
and roles
5 0.576 0.878 0.534 0.132 0.469 1.423 6.541 0.0025
Average score 5 0.6312 0.8492 0.4326 0.2512 0.544 1.6941 6.4461 0.0031
The results in Table 4.11 show that the averages mean score for the ownership and
shareholding for the firms under DSE is 0.6312. Presence of outside block holders (more
than 10%) had an overall mean score of .613 and SD =.1241In addition, the results show
115
that the DSE firms surveyed the CEO own shares (mean score=.744, SD=.3311).
Directors ownership (block ownership) other than the CEO and Chairman (mean
score=.542, SD=.341), Chairman or CEO is block holder (10%) (mean score=.625,
SD=.234) and Concentration of ownership (top five) (mean score=.678, SD=.3324).
Dividend policy (mean score=.593, SD= .3541), Disclosure of staff benefits other than
wages and salaries (mean score=.679, SD= .342), Disclosure of company secretary in
annual report with description of duties and roles (mean score=.576, SD= .132). From
skewness, the study observed that the average score of ownership and shareholding are
positively skewed (.544) and is very near to zero which clarified that the constructs are
asymmetrical. Kurtosis values indicated that all the sub constructs have platy-kurtic
distribution and it is concluded that they are normally distributed (1.694).
The index score for companies listed at DSE was 63.12% which was not very high i.e. it
less than 70%. High ownership and shareholding increases firms’ value especially when
the Chairman, Directors and CEO share ownership due to the incentive effective.
Investors with large ownership stakes have strong incentive to maximize their firms’
value and are able to collect information and to oversee managers, and this can help
overcome the principal-agent problem. The presence of large amount of block holders
suggests that there is effective monitoring from investor on firm’s major decision that
helps to reduce agency conflicts. The block holders have more capability to influence
management decision. They are able to force management to take actions that are for the
best interest of share holders and maximize their overall wealth. According to Jensen and
Meckling (1976) ownership structure helps to reduce agency conflicts hence aligning the
116
interest of share holder and manager. With high conflict of interest between share holders
and managers the corporate governance mechanism of organization is generally weak.
Table 4.12: Ownership and Shareholding (UGANDA-USE)
N
Mea
n
Max
imum
Min
imum
Std
. Dev
.
Ske
wne
ss
Kur
tosi
s
Jar
que-
Ber
a
Pro
babi
lit
y
Presence of
outside stock
holders
6 0.812 0.878 0.532 0.2243 0.492 1.342 9.456 0.0021
The CEO own
shares
6 0.855 0.892 0.521 0.2516 0.456 1.731 6.311 0.0022
Directors
ownership
6 0.641 0.732 0.542 0. 242 0.382 1.325 3.527 0.0021
Chairman or CEO
is block holder
(10%)
6 0.723 0.861 0.422 0.2441 0.473 1.313 7.476 0.0020
Concentration of
ownership (top
five)
6 0.674 0.718 0.412 0.4322 0.386 -1.113 7.456 0.0051
Dividend policy 6 0.643 0.723 0.442 0.2532 0.434 1.534 8.341 0.0010
Disclosure of staff
benefits other
than wages and
salaries
6 0.672 0.745 0.431 0. 364 0.471 -2.534 9.414 0.0031
Disclosure of
company
secretary
6 0.674 0.765 0.432 0.1356 0.367 2.521 7.541 0.0013
Average score
6 0.712 0.789 0.466 0.256 0.433 0.765 7.441 0.002
117
The results in Table 4.12 show that the average mean score for the ownership and
shareholding for the firms under USE is 0.712. Presence of outside block holders (more
than 10%) had an overall mean score of .812 and SD =.2243In addition, the results show
that the NSE firms surveyed the CEO own shares (mean score=.855, SD=.2516).
Directors ownership (block ownership) other than the CEO and Chairman (mean
score=.641, SD=.242), Chairman or CEO is block holder (10%) (mean score=.723,
SD=.2441) and Concentration of ownership (top five) (mean score=.674, SD=.4322).
Dividend policy (mean score=.643, SD= .2532), Disclosure of staff benefits other than
wages and salaries (mean score=.672, SD= .364), Disclosure of company secretary in
annual report with description of duties and roles (mean score=.674, SD= .1356). From
skewness, the study observed that the average score of ownership and shareholding are
positively skewed (.433) and is very near to zero which clarified that the constructs are
asymmetrical. Kurtosis values indicated that all the sub constructs have platy-kurtic
distribution and it is concluded that they are normally distributed (.765).
The index score for companies listed at USE was 71.2%. The ownership and
shareholding includes the presence of outside block holders, large shareholders are
argued to monitor the management better than small shareholders as they internalize
larger part of the monitoring costs and have sufficient voting power to influence
corporate decisions.
118
Table 4.13: Ownership and Shareholding RWANDA-RSE
N
Mea
n
Max
imum
Min
imum
Std
. Dev
.
Ske
wne
ss
Kur
tosi
s
Jar
que-
Ber
a
Pro
babi
lity
Presence of outside
blockholders
2 0.635 0.743 0.433 0.1243 0.342 2.042 3.581 0.0192
The CEO own
shares
2 0.592 0.625 0.521 0.1318 0.422 2.113 4.311 0.0014
Directors
ownership
2 0.541 0.638 0.541 0. 142 0.592 2.421 7.416 0.0037
Chairman or CEO
is block holder
2 0.613 0.734 0.532 0.128 0.491 2.314 5.488 0.0032
Concentration of
ownership
2 0.633 0.785 0.522 0.1232 0.024 3.131 3.482 0.0684
Dividend policy 2 0.582 0.623 0.512 0.1212 0.421 3.224 6.322 0.0042
Disclosure of staff
benefits
2 0.441 0.611 0.441 0. 242 0.395 3.461 6.413 0.0031
Disclosure of CS 2 0.612 0.733 0.533 0.2322 0.494 2.312 7.435 0.0013
Average score 2 0.581 0.686 0.504 0.143 0.395 2.627 5.556 0.013
The results in Table 4.13 show that the average mean score for the ownership and
shareholding for the firms under RSE is 0.581. Presence of outside block holders (more
than 10%) had an overall mean score of .635 and SD =.1243In addition, the results show
that the NSE firms surveyed the CEO own shares (mean score=.592, SD=.1318).
Directors ownership (block ownership) other than the CEO and Chairman (mean
score=.541, SD=.142), Chairman or CEO is block holder (10%) (mean score=.613,
SD=.128) and Concentration of ownership (top five) (mean score=.633, SD=.1232).
Dividend policy (mean score=.582, SD= .1212), Disclosure of staff benefits other than
119
wages and salaries (mean score=.582, SD= .1212), Disclosure of company secretary in
annual report with description of duties and roles (mean score=.441, SD= .242). From
skewness, the study observed that the average score of ownership and shareholding are
positively skewed (.395) and is very near to zero which clarified that the constructs are
asymmetrical. Kurtosis values indicated that all the sub constructs have platy-kurtic
distribution and it is concluded that they are normally distributed (2.627).
Ownership and shareholding includes presence of outside block holders owning more
than 10% of shareholding, CEO owning shares, directors ownership, chairman or CEO
are block holders, concentration of ownership, disclosure of staff remuneration and
disclosure of the company’s annual report. The index score for companies listed at RSE
was 58.10% which was just above average. High ownership concentration may lead to
the extraction of the firm’s resources by the dominant owners at the expense of other
shareholders. The presence of block holders improves CG especially when the percentage
is high in that the monitoring of the management will improve. The block holders have
more capability to influence management decision. They are able to force management to
take actions that are for the best interest of share holders and maximize their overall
wealth. According to Jensen and Meckling (1976) ownership structure helps to reduce
agency conflicts hence aligning the interest of share holder and manager. With high
conflict of interest between share holders and managers the corporate governance
mechanism of organization is generally weak.
120
Table 4.14: Transparency, Disclosures and Auditing (KENYA-NSE)
N
Mea
n
Max
imum
Min
imum
Std
. Dev
.
Ske
wne
ss
Kur
tosi
s
Jar
que-
Ber
a
Pro
babi
lity
The company have
full disclosure of
CG practices
43 0.734 0.787 0.131 0.6247 0.039 1.034 3.581 0.0695
Disclosure of
payment to auditors
for consulting and
other work
43 0.799 0.821 0.221 0.1318 0.729 2.225 9.311 0.0022
Internal audit
committee
43 0.843 0.732 0.342 0. 242 0.897 2.567 8.416 0.0027
Board of directors
and executive staff
members
remuneration
43 0.819 0.884 0.732 0.138 0.598 1.314 7.488 0.0022
Annual report of
share ownership
43 0.734 0.886 0.222 0.3241 0.028 2.131 5.482 0.0284
Employee
ownership
43 0.888 0.722 0.111 0.1311 0.529 1.224 6.322 0.0032
Auditor
appointment and
rotation
43 0.742 0.831 0.441 0. 342 0.797 2.461 7.413 0.0011
Annual reports
through internet
43 0.711 0.832 0.633 0.3321 0.693 2.312 8.435 0.0023
Disclosure of other
events in the
internet
43 0.735 0.883 0.432 0.525 0.033 2.031 6.567 0.078
Chairman’s
statement
43 0.793 0.824 0.522 0.3316 0.529 2.214 7.313 0.036
Average score
43 0.779 0.820 0.378 0.317 0.487 1.951 7.032 0.024
121
The results in Table 4.14 yield an overall mean score of .779. The overall mean score of
.734 shows that the firms under NSE have full disclosure of CG practices. In addition, the
results show that the NSE firms surveyed have disclosure of payment to auditors for
consulting and other work (mean score=.799, SD=.1318). Internal audit committee (mean
score=.843, SD=.242), board of directors and executive staff members remuneration
(mean score=.819, SD=.138) and that annual report of share ownership (mean
score=.734, SD=.3241). Employee ownership (mean score=.888, SD= .1311), auditor
appointment and rotation (mean score=.742, SD= .342), annual reports through internet
(mean score=.711, SD= .3221), disclosure of other events in the internet (mean
score=.735, SD= .525) and chairman’s statement (mean score=.793, SD= .3316) is
indicated. From skewness, the study observed that the average score of transparency,
disclosures and auditing constructs are positively skewed (.487) and is very near to zero
which clarified that the constructs are asymmetrical. Kurtosis values indicated that all the
sub constructs have platy-kurtic distribution and it is concluded that they are normally
distributed (1.951).
Transparency, disclosure and auditing constitutes; disclosure of CG practices, auditors
payments, internal audit committee, BOD and executive staff members remuneration,
annual report of share ownership and employee ownership, auditors appointment and
rotation, and disclosure of annual report and other events in the internet. The mean CGI
score was 77.9% for companies listed at NSE. Companies listed at NSE are normally
required to adhere with the NSE and CMA listing requirements and that is the reason
why the score for this variable is high. Recent research suggests that the extended of
122
disclosure and transparency is important for effective CG. La Porta et al. (2000) found
that that the protection of shareholders and creditors by the legal system is important in
controlling shareholding therefore improving CG. The findings of the study are in line
with existing literature which posits that transparency and disclosure requirements affects
firm performance.
Table 4.15: Transparency, Disclosures and Auditing (TANZANIA-DSE)
N
Mea
n
Max
imu
m
Min
imu
m
Std
. D
ev.
Ske
wn
ess
Ku
rto
sis
Jar
qu
e-B
era
Pro
bab
ility
Disclosure of CG
practices
5 0.713 0.876 0.532 0.1241 0.495 2.044 8.492 0.0034
Disclosure of
payment to auditors
5 0.744 0.853 0.322 0.1311 0.623 2.441 7.322 0.0021
Internal audit
committee
5 0.742 0.831 0.443 0. 141 0.592 2.335 5.527 0.0022
BOD and executive
staff members
remuneration
5 0.825 0.871 0.521 0.2343 0.575 1.411 6.476 0.0031
Annual report of
share ownership
5 0.778 0.838 0.332 0.3324 0.285 1.133 6.456 0.0042
Employee ownership 5 0.693 0.789 0.545 0.3541 0.425 1.234 7.341 0.0021
Auditor appointment
and rotation
5 0.779 0.858 0.332 0. 342 0.593 1.532 6.414 0.0012
Annual reports
through internet
5 0.776 0.878 0.534 0.1323 0.469 2.423 5.541 0.0025
Disclosure of other
events
5 0.748 0.863 0.423 0.422 0.445 2.241 6.641 0.028
Chairman’s statement 5 0.894 0.897 0.443 0.4314 0.531 1.243 5.323 0.013
Average 5 0.769 0.855 0.442 0.270 0.503 1.803 6.55 0.0061
123
The results in Table 4.15 yield an overall mean score of .769. The overall mean score of
.734 shows that the firms under DSE have full disclosure of CG practices. In addition, the
results show that the DSE firms surveyed have disclosure of payment to auditors for
consulting and other work (mean score=.799, SD=.1318). Internal audit committee (mean
score=.843, SD=.242), board of directors and executive staff members remuneration
(mean score=.819, SD=.138) and that annual report of share ownership (mean
score=.734, SD=.3241). Employee ownership (mean score=.888, SD= .1311), auditor
appointment and rotation (mean score=.742, SD= .342), annual reports through internet
(mean score=.711, SD= .3221), disclosure of other events in the internet (mean
score=.735, SD= .525) and chairman’s statement (mean score=.793, SD= .3316) is
indicated. From skewness, the study observed that the average score of board structure
and composition constructs are positively skewed (.503) and is very near to zero which
clarified that the constructs are asymmetrical. Kurtosis values indicated that all the sub
constructs have platy-kurtic distribution and it is concluded that they are normally
distributed (1.803)
Transparency, disclosure and auditing constitute; disclosure of CG practices, auditors
payments, internal audit committee, BOD and executive staff members remuneration,
annual report of share ownership and employee ownership, auditors appointment and
rotation, and disclosure of annual report and other events in the internet. The mean CGI
score was 76.9% for companies listed at DSE. Companies listed at DSE are normally
required to adhere with the DSE and CMSA listing requirements and that is the reason
why the score for this variable is high. Recent research suggests that the extended of
124
disclosure and transparency is important for effective CG. La Porta et al. (2000) found
that that the protection of shareholders and creditors by the legal system is important in
controlling shareholding therefore improving CG. The findings of the study are in line
with existing literature which posits that transparency and disclosure requirements affects
firm performance.
Table 4.16: Transparency, Disclosures and Auditing (UGANDA-USE)
N
Mea
n
Max
imu
m
Min
imu
m
Std
. D
ev.
Ske
wn
ess
Ku
rto
sis
Jar
qu
e-B
era
Pro
bab
ility
The company have
full disclosure of CG
6 0.812 0.878 0.732 0.2243 0.492 1.342 10.456 0.0031
Disclosure of
payment to auditors
6 0.855 0.892 0.521 0.2516 0.456 1.731 7.311 0.0032
Internal audit
committee
6 0.641 0.732 0.542 0. 242 0.382 1.325 4.527 0.0031
Board of directors
and executive
remuneration
6 0.723 0.861 0.422 0.2441 0.373 1.313 8.476 0.0030
Annual report of
share ownership
6 0.674 0.718 0.412 0.4322 0.386 -1.113 8.456 0.0071
Employee ownership 6 0.643 0.723 0.442 0.2532 0.434 1.534 9.341 0.0020
Auditor appointment
and rotation
6 0.672 0.745 0.431 0. 364 0.471 -2.534 10.414 0.0041
Annual reports
through internet
6 0.674 0.765 0.432 0.1356 0.367 2.521 8.541 0.0023
Disclosure of other
events in the internet
6 0.743 0.854 0.431 0.125 0.465 3.342 11.641 0.046
Chairman’s statement 6 0.845 0.878 0.412 0.1315 0.531 -3.254 13.323 0.032
Average score
6 0.728 0.804 0.477 0.224 0.435 0.620 9.248 0.0105
125
The results in Table 4.16 yield an overall mean score of .728. The overall mean score of
0.812 shows that the firms under USE have full disclosure of CG practices. In addition,
the results show that the USE firms surveyed have disclosure of payment to auditors for
consulting and other work (mean score=0.855, SD=0.2516). Internal audit committee
(mean score=0.641, SD=0. 242),board of directors and executive staff members
remuneration (mean score=0.723, SD=0.2441) and that annual report of share ownership
(mean score=0.674, SD=0.4322). Employee ownership (mean score=.888, SD= .1311),
auditor appointment and rotation (mean score=0.643, SD= 0.2532), annual reports
through internet (mean score=0.672, SD= 0. 364), disclosure of other events in the
internet (mean score=0.674, SD= 0.1356) and chairman’s statement (mean score=0.743,
SD= 0.125) is indicated. From skewness, the study observed that the average score of
board structure and composition constructs are positively skewed (0.435) and is very near
to zero which clarified that the constructs are asymmetrical. Kurtosis values indicated
that all the sub constructs have platy-kurtic distribution and it is concluded that they are
normally distributed (0.620).
The mean CGI score was 72.8% for companies listed at USE. Companies listed at USE
are normally required to adhere with the USE and CMA listing requirements and that is
the reason why the score for this variable is high. Transparency, disclosure and auditing
constitute constitutes the disclosure of CG practices, auditors payments, internal audit
committee, BOD and executive staff members remuneration, annual report of share
ownership and employee ownership, auditors appointment and rotation, and disclosure of
annual report and other events in the internet. Recent research suggests that the extended
126
of disclosure and transparency is important for effective CG. La Porta et al. (2000) found
that that the protection of shareholders and creditors by the legal system is important in
controlling shareholding therefore improving CG. The findings of the study are in line
with existing literature which posits that transparency and disclosure requirements affects
firm performance
Table 4.17: Transparency, Disclosures and Auditing (RWANDA-RSE)
N
Mea
n
Max
imu
m
Min
imu
m
Std
. D
ev.
Ske
wn
ess
Ku
rto
sis
Jar
qu
e-B
era
Pro
bab
ility
Disclosure of CG
practices
2 0.635 0.943 0.433 0.1243 0.342 2.042 3.581 0.0192
Disclosure of
payment to auditors
2 0.592 0.825 0.321 0.1318 0.322 2.113 4.311 0.0014
Internal audit
committee
2 0.541 0.838 0.441 0. 142 0.392 2.421 7.416 0.0017
BOD and executive
staff members
remuneration
2 0.613 0.934 0.432 0.238 0.491 2.314 5.488 0.0012
Annual report of
share ownership
2 0.633 0.985 0.322 0.1242 -0.034 3.131 5.482 0.0184
Employee ownership 2 0.582 0.823 0.412 0.2312 0.421 3.224 6.322 0.0022
Auditor appointment
and rotation
2 0.641 0.811 0.441 0. 242 0.395 3.461 7.413 0.0021
Annual reports
through internet
2 0.612 0.933 0.333 0.2322 0.494 4.312 6.435 0.0033
Disclosure of other
events
2 0.634 0.953 0.332 0.1251 0.142 4.031 4.567 0.038
Chairman’s statement 2 0.692 0.923 0.322 0.1511 0.345 3.214 5.313 0.016
Average 2 0.617 0.896 0.378 0.169 0.331 3.026 5.632 0.010
127
The results in Table 4.17 yield an overall mean score of .617. The overall mean score of
.635 shows that the firms under RSE have full disclosure of CG practices. In addition, the
results show that the RSE firms surveyed have disclosure of payment to auditors for
consulting and other work (mean score=.592, SD=.1318). Internal audit committee (mean
score=.843, SD=.242), board of directors and executive staff members remuneration
(mean score=.819, SD=.138) and that annual report of share ownership (mean
score=.734, SD=.3241). Employee ownership (mean score=.888, SD= .1311), auditor
appointment and rotation (mean score=.742, SD= .342), annual reports through internet
(mean score=.711, SD= .3221), disclosure of other events in the internet (mean
score=.735, SD= .525) and chairman’s statement (mean score=.793, SD= .3316) is
indicated. From skewness, the study observed that the average score of board structure
and composition constructs are positively skewed (0.331) and is very near to zero which
clarified that the constructs are asymmetrical. Kurtosis values indicated that all the sub
constructs have platy-kurtic distribution and it is concluded that they are normally
distributed (3.026).
Transparency, disclosure and auditing constitute; disclosure of CG practices, auditors
payments, internal audit committee, BOD and executive staff members remuneration,
annual report of share ownership and employee ownership, auditors appointment and
rotation, and disclosure of annual report and other events in the internet. The mean CGI
score was 61.7% for companies listed at RSE. Companies listed at RSE are normally
required to adhere with the RSE and CMA listing requirements and that is the reason why
the score for this variable is high.
128
Table 4.18: Board Remuneration (KENYA-NSE)
N
Mea
n
Max
imu
m
Min
imu
m
Std
. D
ev.
Ske
wn
ess
Ku
rto
sis
Jar
qu
e-B
era
Pro
bab
ility
Remuneration
committee
43 0.834 0.987 0.431 0.3247 0.798 2.134 8.581 0.0493
Composition of the
remuneration
committee
43 0.899 0.951 0.421 0.3318 0.725 2.225 7.311 0.0022
Policy framework for
the remunerating
committee
43 0.843 0.932 0.342 0. 242 0.896 2.567 7.416 0.0027
Remuneration
committee comprises
non-executive board
members
43 0.819 0.964 0.632 0.338 0.588 2.314 6.488 0.0022
CEO compensation
is disclosed
43 0.634 0.886 0.422 0.3241 0.364 2.131 7.482 0.0384
Compensation in
form of stock bonus
43 0.888 0.912 0.311 0.3311 0.527 2.224 8.322 0.0012
Loans or advances to
board members not
provided
43 0.742 0.881 0.441 0. 342 0.794 2.461 7.413 0.0011
Balance between
guaranteed salary and
performance element
(share option)
43 0.711 0.892 0.433 0.3321 0.643 2.312 6.435 0.0023
Remuneration policy
disclosed in annual
report
43 0.835 0.963 0.432 0.325 0.542 2.031 7.567 0.038
Majority of the
remuneration
committee members
are non-executive
43 0.993 0.954 0.422 0.3316 0.534 1.214 8.313 0.026
Average score
43 0.819 0.932 0.428 0.329 0.641 2.161 7.532 0.0163
129
he results in Table 4.18 yield an overall mean score of 0.819 and SD=0.329 on board
remuneration. Remuneration committee (Mean score=0.834, SD=0.3247), Composition
of the remuneration committee (Mean=0.899, SD=0.3318), Policy framework for the
remunerating committee (Mean=0.843, SD=0. 242), Remuneration committee comprises
non-executive board members (Mean=0.819, SD=0.338). Further the findings indicates
that CEO compensation is disclosed (Mean=0.634, SD=0.3241, Compensation in form
of stock bonus (Mean=0.888, SD=0.3311), loans or advances to board members not
provided (Mean=0.742, SD=0. 342). The results further indicated that balance between
guaranteed salary and performance element (share option)(Mean=0.711, SD=0.3321),
Remuneration policy disclosed in annual report (Mean=0.835, SD=0.325) and that
majority of the remuneration committee members are non-executive
(Mean=0.993,SD=0.3316).From skewness, the study observed that the average score of
board structure and composition constructs are positively skewed (0.641) which clarified
that the constructs are asymmetrical. Kurtosis values indicated that all the sub constructs
have platy-kurtic distribution and it is concluded that they are normally distributed
(2.161).
The development of compensation plans that tie management compensation directly to
the firm performance is often suggested as the solution to the inefficient management.
The compensation plans can come in form of stock price performance which generally
reduces the agency problem in a firm. The effective of the payment plans are normally
enhanced by the disclosure of the BOD remuneration and the composition of the
remuneration committee. Companies listed at NSE have a mean CGI score of 81.9% with
130
the highest score being 99.3% that of majority of the remuneration committee members
being non-executive, this is in line with the CMA requirements and it is supported by
literature. However, conflict of interest arises as directors pay themselves large
compensation packages, at the expense of shareholders. Therefore disclosure of board
and management compensation is one of the monitoring mechanisms, commonly
included in most corporate governance codes.
OECD (2004) states that the board should assume the function of aligning key executive
and board remuneration with the long-term interests of the company and its shareholders
and encourages boards to assess, at least annually, the performance of the board as a
group, as well as the performance of each board member and the senior executive
officers. Companies are encouraged to link performance and remuneration and provide
disclosure in their annual reports about performance against objectives and remuneration
in relation to performance. This disclosure is expected to increase transparency and
improve the ability of the shareholders to evaluate the compensation packages of
directors and ultimately prevent the directors from enriching themselves at the expense of
the shareholders.
131
Table 4.19: Board Remuneration (TANZANIA-DSE)
N
Mea
n
Max
imu
m
Min
imu
m
Std
. D
ev.
Ske
wn
ess
Ku
rto
sis
Jar
qu
e-
Ber
a
Pro
bab
ility
Remuneration
committee
5 0.713 0.876 0.232 0.1242 0.395 2.044 8.492 0.0024
Composition of the
committee
5 0.744 0.853 0.222 0.2311 0.323 2.441 9.322 0.0031
Policy framework 5 0.742 0.831 0.143 0. 241 0.492 2.335 7.527 0.0032
Remuneration
committee comprises
NED
5 0.825 0.871 0.421 0.2343 0.375 2.411 8.476 0.0031
CEO compensation is
disclosed
5 0.778 0.838 0.432 0.2321 0.385 1.133 11.456 0.0052
Compensation in form
of stock bonus
5 0.693 0.889 0.345 0.2541 0.425 2.234 9.341 0.0021
Loans or advances to
board members not
provided
5 0.779 0.958 0.332 0. 242 0.393 1.532 8.414 0.0012
Balance between
guaranteed salary and
performance
5 0.776 0.878 0.334 0.1323 0.469 2.423 9.541 0.0015
Remuneration policy 5 0.748 0.863 0.423 0.322 0.445 2.241 8.641 0.028
Remuneration
committee
5 0.794 0.897 0.443 0.2314 0.431 2.243 8.323 0.013
Average score 5 0.759 0.875 0.332 0.220 0.413 2.104 8.953 0.006
The study further observed that the overall mean score of board remuneration in DSE is
(Mean=0.759, SD=0.220). Further the study observed that remuneration committee
(Mean=0.713, SD=0.1242), Composition of the remuneration committee (Mean=0.744,
SD=0.2311), Policy framework for the remunerating committee (Mean=0.742, SD=0.
241), remuneration committee comprises non-executive board members (Mean=0.825,
SD=0.2343). Further CEO compensation is disclosed (Mean=0.778, SD=0.2321),
132
Compensation in form of stock bonus (Mean=0.693, SD=0.2541), Loans or advances to
board members not provided (Mean=0.779, SD=0. 242), balance between guaranteed
salary and performance element (share option) (Mean=0.776, SD=0.1323),Remuneration
policy disclosed in annual report (Mean=0.748, SD=0.322) and that majority of the
remuneration committee members are non-executive (Mean=0.794, SD=0.2314).
Companies listed at DSE have a mean CGI score of 75.9% with the highest score being
82.5% that of majority of the remuneration committee members being non-executive, this
is in line with the CMA requirements and it is supported by literature. However, conflict
of interest arises as directors pay themselves large compensation packages, at the expense
of shareholders. Therefore disclosure of board and management compensation is one of
the monitoring mechanisms, commonly included in most corporate governance codes.
Table 4.20: Board Remuneration (UGANDA-USE)
N
Mea
n
Max
imu
m
Min
imu
m
Std
. D
ev.
Ske
wn
ess
Ku
rto
sis
Jar
qu
e-B
era
Pro
bab
ility
Remuneration committee 6 0.612 0.878 0.432 0.2243 0.392 1.342 11.456 0.0021
Composition of the com. 6 0.655 0.892 0.521 0.2516 0.356 1.731 9.311 0.0012
Policy framework 6 0.741 0.872 0.442 0. 242 0.282 1.325 8.527 0.0021
Remuneration com.
comprises NED
6 0.623 0.861 0.322 0.2441 0.373 1.313 8.476 0.0020
CEO compensation 6 0.674 0.858 0.412 0.3322 0.386 2.113 6.456 0.0041
stock bonus 6 0.643 0.863 0.442 0.2532 0.334 2.534 7.341 0.0020
Loans or advances 6 0.672 0.855 0.431 0. 364 0.471 2.534 8.414 0.0031
salary and performance 6 0.674 0.875 0.432 0.3356 0.367 2.521 9.541 0.0013
Remuneration policy 6 0.743 0.874 0.431 0.125 0.365 2.342 8.641 0.026
Remuneration committee 6 0.845 0.938 0.412 0.3315 0.431 1.254 7.323 0.022
Average score 6 0.688 0.876 0.427 0.262 0.375 1.901 8.548 0.007
133
The overall mean score of the firms in USE is 0.688 with an overall SD of 0.262. Further
remuneration committee (Mean=0.612, SD=0.2243), composition of the remuneration
committee (Mean=0.655, SD=0.2516), Policy framework for the remunerating committee
(Mean=0.741, SD=0. 242), remuneration committee comprises non-executive board
members (Mean=0.623, SD=0.2441), CEO compensation is disclosed (Mean=0.674,
SD=0.3322), Compensation in form of stock bonus (Mean 0.643, SD=0.2532), loans or
advances to board members not provided (Mean=0.672, SD=0. 364), balance between
guaranteed salary and performance element (share option)(Mean=0.674, SD=0.3356),
remuneration policy disclosed in annual report (Mean=0.743, SD=0.125) and that
majority of the remuneration committee members are non-executive (Mean=0.845,
SD=0.3315).
Companies listed at USE have a mean CGI score of 68.8% with the highest score being
84.5% that of majority of the remuneration committee members being non-executive, this
is in line with the CMA requirements and it is supported by literature. However, conflict
of interest arises as directors pay themselves large compensation packages, at the expense
of shareholders. Therefore disclosure of board and management compensation is one of
the monitoring mechanisms, commonly included in most corporate governance codes.
134
Table 4.21: Board Remuneration (RWANDA-RSE)
N
Mea
n
Max
imu
m
Min
imu
m
Std
. D
ev.
Ske
wn
ess
Ku
rto
sis
Jar
qu
e-
Ber
a
Pro
bab
ilit
y
Remuneration
committee
2 0.688 0.747 0.432 0.1243 0.242 2.043 5.581 0.0191
Composition of the
remuneration
committee
2 0.674 0.824 0.361 0.1318 0.222 2.112 4.311 0.0014
Policy framework 2 0.688 0.832 0.481 0. 142 0.392 2.422 7.416 0.0027
Remuneration
committee comprises
NED
2 0.712 0.854 0.432 0.238 0.391 2.312 7.488 0.0022
CEO compensation
is disclosed
2 0.721 0.835 0.522 0.1242 -0.345 2.132 5.482 0.0224
Compensation in
form of stock bonus
2 0.721 0.823 0.412 0.2312 0.421 2.223 6.322 0.0022
Loans or advances to
board members
2 0.642 0.788 0.441 0. 142 0.395 2.462 7.413 0.0021
Balance between
guaranteed salary and
performance
2 0.613 0.734 0.333 0.2322 0.494 2.313 7.435 0.0013
Remuneration policy 2 0.759 0.846 0.332 0.1251 0.423 2.032 6.567 0.028
Remuneration
committee
2 0.783 0.862 0.322 0.1511 0.541 2.215 6.313 0.014
Average score
2 0.703 0.815 0.406 0.169 0.317 2.226 6.433 0.009
The study further revealed that under RSE the overall mean score of board remuneration
(Mean=0.703, SD=0.169). The study further observed that remuneration committee
(Mean=0.688, SD=0.1243), composition of the remuneration committee (Mean=0.674,
SD=0.1318), Policy framework for the remunerating committee (Mean=0.688, SD=0.
142), remuneration committee comprises non-executive board members (Mean=0.712,
135
SD=0.238), CEO compensation is disclosed (Mean=0.721, SD=0.1242), compensation
in form of stock bonus (Mean=0.721, SD=0.2312), loans or advances to board members
not provided (Mean=0.642, SD=0. 142), balance between guaranteed salary and
performance element (share option)(Mean=0.613, SD=0.2322), remuneration policy
disclosed in annual report (Mean=0.759, SD=0.1251) and that majority of the
remuneration committee members are non-executive (Mean=0.783, SD=0.1511).
Companies listed at USE have a mean CGI score of 70.3% with the highest score being
78.3% that of majority of the remuneration committee members being non-executive, this
is in line with the CMA requirements and it is supported by literature. CG can improve
firm performance and this is supported by literature Weisbach (1998) stated that incentive
based compensation to directors influence the level of performance.
Table 4.22: Corporate Ethics (KENYA-NSE)
N
Mea
n
Max
imu
m
Min
imu
m
Std
. D
ev.
Ske
wn
ess
Ku
rto
sis
Jar
qu
e-
Ber
a
Pro
bab
ility
Corporate ethics committee 43 0.834 0.987 0.331 0.2247 0.392 2.034 6.581 0.0215
Code of ethical conduct 43 0.849 0.931 0.421 0.2318 0.429 1.225 3.311 0.0022
Code of conduct 43 0.823 0.932 0.432 0. 242 0.497 1.567 2.416 0.0027
Notice of AGM 43 0.912 0.964 0.432 0.138 0.698 4.314 9.488 0.0022
Agenda of the AGM 43 0.844 0.953 0.422 0.3241 0.338 2.131 5.482 0.0424
Compliance with CMA 43 0.882 0.732 0.311 0.3311 0.429 2.224 6.322 0.0032
SCR 43 0.883 0.821 0.341 0. 342 0.597 1.461 7.413 0.0011
company’s code of ethics 43 0.863 0.822 0.633 0.3321 0.593 1.312 6.435 0.0023
Average score 43 0.861 0.893 0.415 0.264 0.497 2.034 5.931 0.009
136
The study observed that the average score of corporate ethics for firms listed at the NSE
is (Mean=0.861, SD=0.264). Further corporate ethics committee in place (Mean=0.834,
SD=0.2247, code of ethical conduct (Mean=0.849, SD=0.2318), Code of conduct is
published (Mean=0.823, SD=0. 242), notice of annual general meeting (Mean=0.912,
SD=0.138), agenda of the annual general meeting (Mean=0.844, SD=0.3241, compliance
with CMA guidelines (Mean=0.882, SD=0.3311), environmental and social
responsibility (Mean=0.883, SD=0. 342) and that disclosure of adherence to the
company’s code of ethics (Mean=0.863, SD=0.3321).
Corporate ethics includes; corporate ethics committee, code of ethical conduct, notice and
agenda of AGM, compliance with CMA guidelines, environmental and social
responsibility, and disclosure and adherence to the company’s code of ethics. The CG
practices suggest that the board of director should meet regularly, with due notice of
issues to be discussed and should record its conclusion in discharging it duties and
responsibilities. The practice also suggested that details of attendance of the directors are
revealed in annual report during the financial year to make sure the directors are
committed to be part of the company. In the study, it was found that majority of the
companies complied very well with the practice after the CG was implemented compared
to before the code was introduced.
137
Table 4.23: Corporate Ethics (TANZANIA-DSE)
N
Mea
n
Max
imum
Min
imum
Std
. Dev
.
Ske
wne
ss
Kur
tosi
s
Jar
que-
Ber
a
Pro
babi
lity
Corporate ethics
committee in place
5 0.804 0.929 0.232 0.1241 0.495 2.044 11.492 0.0024
Code of ethical
conduct
5 0.821 0.944 0.522 0.2311 0.623 2.441 9.322 0.0021
Code of conduct is
published
5 0.811 0.921 0.443 0. 241 0.592 2.335 4.527 0.0012
Notice of annual
general meeting
5 0.823 0.952 0.521 0.2343 0.575 1.411 7.476 0.0031
Agenda of the annual
general meeting
5 0.772 0.912 0.532 0.2324 0.485 1.133 8.456 0.0032
Compliance with
CMA guidelines
5 0.892 0.841 0.545 0.2541 0.425 2.234 9.341 0.0021
Environmental and
social responsibility
5 0.779 0.922 0.532 0. 242 0.593 2.532 5.414 0.0012
Disclosure of
adherence to the
company’s code of
ethics
5 0.776 0.921 0.534 0.3323 0.469 2.423 6.541 0.0025
Average score 5 0.809 0.917 0.482 0.234 0.533 2.069 7.823 0.002
The firms listed at DSE yielded an average mean of 0.809 and SD of .234 under
corporate ethics. Further corporate ethics committee in place (Mean=0.804, SD=0.1241),
Code of ethical conduct (Mean=0.821, SD=0.2311), code of conduct is published
(Mean=0.811, SD=0. 241), notice of annual general meeting (Mean=0.823, SD=0.2343),
agenda of the annual general meeting (Mean=0.772, SD=0.2324), compliance with CMA
guidelines (Mean=0.892, SD=0.2541), environmental and social responsibility
138
(Mean=0.779, SD=0. 242) and disclosure of adherence to the company’s code of ethics
(Mean=0.776, SD=0.3323).
Corporate ethics includes; corporate ethics committee, code of ethical conduct, notice and
agenda of AGM, compliance with CMSA guidelines, environmental and social
responsibility, and disclosure and adherence to the company’s code of ethics. The mean
score for companies listed at DSE was 80.9% with the being 89.2% i.e. compliance to
CMA guidelines.
Table 4.24: Corporate Ethics (UGANDA-USE)
N
Mea
n
Max
imum
Min
imum
Std
. Dev
.
Ske
wne
ss
Kur
tosi
s
Jar
que-
Ber
a
Pro
babi
lity
Corporate ethics
committee in place
6 0.712 0.878 0.432 0.2243 0.392 1.342 9.456 0.0021
Code of ethical
conduct
6 0.755 0.892 0.421 0.2516 0.356 1.731 8.311 0.0012
Code of conduct is
published
6 0.841 0.932 0.442 0. 242 0.282 2.325 6.527 0.0021
Notice of annual
general meeting
6 0.723 0.861 0.422 0.2441 0.373 2.113 7.476 0.0020
Agenda of AGM 6 0.724 0.818 0.412 0.2322 0.286 2.113 7.456 0.0041
Compliance with
CMA guidelines
6 0.643 0.823 0.442 0.1532 0.334 1.534 8.341 0.0010
Environmental and
social responsibility
6 0.672 0.745 0.431 0. 164 0.471 2.534 7.414 0.0021
Disclosure of
adherence code
6 0.674 0.821 0.332 0.3356 0.267 2.521 7.541 0.0013
Average score 6 0.718 0.846 0.416 0.240 0.345 2.026 7.815 0.005
139
The corporate ethics under firms listed at USE yielded an average mean of 0.718 and SD
of 0.240. Further under individual sub-constructs, corporate ethics committee in place
(Mean=0.712, SD=0.2243), code of ethical conduct (Mean=0.755, SD=0.2516), code of
conduct is published (Mean=0.841, SD=0. 242), notice of annual general meeting
(Mean=0.723, SD=0.2441), agenda of the annual general meeting (Mean=0.724,
SD=0.2322), compliance with CMA guidelines (Mean=0.643, SD=0.1532),
environmental and social responsibility (Mean=0.672, SD=0. 164) and that disclosure of
adherence to the company’s code of ethics (Mean=0.674, SD=0.3356).
Corporate ethics includes; corporate ethics committee, code of ethical conduct, notice and
agenda of AGM, compliance with CMA guidelines, environmental and social
responsibility, and disclosure and adherence to the company’s code of ethics. The mean
score for companies listed at USE was 71.8% with the being 84.1% i.e. published code of
conduct.
140
Table 4.25: Corporate Ethics (RWANDA-RSE))
N
Mea
n
Max
imum
Min
imum
Std
. Dev
.
Ske
wne
ss
Kur
tosi
s
Jar
que-
Ber
a
Pro
babi
lity
Corporate ethics
committee in place
2 0.735 0.943 0.431 0.1213 0.342 2.042 6.581 0.0142
Code of ethical
conduct
2 0.792 0.825 0.371 0.1312 0.422 2.113 4.311 0.0014
Code of conduct is
published
2 0.741 0.838 0.441 0. 143 0.592 2.421 7.416 0.0027
Notice of annual
general meeting
2 0.733 0.934 0.432 0.238 0.491 2.314 5.488 0.0022
Agenda of the annual
general meeting
2 0.723 0.985 0.472 0.1242 0.234 2.131 5.482 0.0424
Compliance with
CMA guidelines
2 0.641 0.823 0.413 0.2312 0.121 2.224 4.322 0.0042
Environmental and
social responsibility
2 0.622 0.811 0.442 0. 242 0.395 2.461 6.413 0.0021
Disclosure of
adherence to the
company’s code of
ethics
2 0.674 0.873 0.332 0.232 0.494 2.312 7.435 0.0013
Average score 2 0.707 0.879 0.416 0.179 0.386 2.252 5.931 0.008
The study further observed that corporate ethics under firms yielded under RSE yielded
an overall mean of 0.707 and SD of 0.179. Further corporate ethics committee in place
(Mean=0.735, SD = 0.1213), code of ethical conduct (Mean=0.792, SD=0.1312), code of
conduct is published (Mean=0.741, SD=0. 143), notice of annual general meeting (Mean
=0.733, SD=0.238), agenda of the annual general meeting (Mean=0.723, SD=0.1242),
compliance with CMA guidelines (Mean=0.641, SD=.2312), environmental and social
responsibility (Mean=0.622, SD=0. 242) and d
code of ethics (Mean=0.674, SD=0.232).
Corporate ethics includes; corporate ethics committee, code of ethical conduct, notice and
agenda of AGM, compliance with CMA guidelines, env
responsibility, and disclosure and adherence to the company’s code of ethics. The mean
score for companies listed at
code of ethical conduct.
from 2009-2013 for the firms listed at the East African Securities exchange i.e. Kenya
(NSE), Tanzania (DSE), Uganda (USE) and Rwanda (RSE). CGI has a value of between
0 and 100, and it is expected that poorly governed firms ha
governed companies have higher scores. The relevant results are as indicated in Table
4.26
Figure 4.2 Corporate Governance Indicators per Securities Exchange
Results from figure 4.2 indicate that the companies listed at the EACSE have high scores
in all the various indicators of CG measured by board structure and composition,
141
0.622, SD=0. 242) and disclosure of adherence to the company’s
0.674, SD=0.232).
Corporate ethics includes; corporate ethics committee, code of ethical conduct, notice and
agenda of AGM, compliance with CMA guidelines, environmental and social
responsibility, and disclosure and adherence to the company’s code of ethics. The mean
score for companies listed at RSE was 70.7% with the being 79.2% i.e. publication of the
The study determined the overall CGI for a five years period
2013 for the firms listed at the East African Securities exchange i.e. Kenya
(NSE), Tanzania (DSE), Uganda (USE) and Rwanda (RSE). CGI has a value of between
0 and 100, and it is expected that poorly governed firms have lower scores, while better
governed companies have higher scores. The relevant results are as indicated in Table
Figure 4.2 Corporate Governance Indicators per Securities Exchange
Results from figure 4.2 indicate that the companies listed at the EACSE have high scores
in all the various indicators of CG measured by board structure and composition,
isclosure of adherence to the company’s
Corporate ethics includes; corporate ethics committee, code of ethical conduct, notice and
ironmental and social
responsibility, and disclosure and adherence to the company’s code of ethics. The mean
publication of the
for a five years period
2013 for the firms listed at the East African Securities exchange i.e. Kenya
(NSE), Tanzania (DSE), Uganda (USE) and Rwanda (RSE). CGI has a value of between
ve lower scores, while better
governed companies have higher scores. The relevant results are as indicated in Table
Figure 4.2 Corporate Governance Indicators per Securities Exchange
Results from figure 4.2 indicate that the companies listed at the EACSE have high scores
in all the various indicators of CG measured by board structure and composition,
142
ownership and shareholding, transparency, disclosures and auditing, board remuneration
and corporate ethics. Under the board structure and composition companies listed at NSE,
DSE and USE tend to have a board size of between 6 and 9 members, role and functions
of the board are clearly spelt out. There are also indications that most of the companies
have the chairman and the CEO functions clearly separated. The boards also consist of
the independent directors. The score for companies listed at RSE was 69.8% which was
lower than for the other securities exchanges because most of the firms actually started
listing from 2009. The ownership and shareholding score among the listed companies is
also high except in RSE where the score is low at 58.1%.
Table 4.26: Overall Corporate Governance Index (2009-2013)
YEARS 2009 2010 2011 2012 2013
NSE 63.6 69.1 72.7 81.8 81.8
DSE 70.9 72.7 80 90.9 90.9
USE 70.9 74.5 78.2 85.5 87.3
RSE 54.5 61.8 67.3 83.7 87.3
Average score 64.975 69.525 74.55 85.475 86.825
The finding indicates that the average score of corporate governance index for the year
2009 was 64.975%, 2010 was 69.525%, 2011 was 74.55%, 2012 was 85.475% with 2013
having the highest 86.825%. In 2009 DSE and USE had the highest corporate governance
index of 70.9%, followed by NSE with RSE having the lowest index. In 2010, USE had
the highest CGI of 74.5%, followed by DSE with an index of 72.7%, NSE with 69.1%
with RSE having the lowest CGI
80%, USE had 78.2%, and NSE
2012, DSE had the highest CGI of 90.9
NSE having the lowest CGI of 81.8
and RSE had 87.3% with NSE having the lo
Figure 4.3 Corporate Governance Index per Country
Results in figure 4.3 indicate
since 2009 as indicated in Table 4.26. In
was 86.825%. The improvements in the score are brought about
awareness i.e. the companies are now more informed about CG.
143
lowest CGI of 61.8%. Further in 2011, DSE had the highest CGI of
and NSE had 72.7% with RSE having the lowest CGI of 67.3
2012, DSE had the highest CGI of 90.9%, USE had 85.5%, and RSE
NSE having the lowest CGI of 81.8%. In 2013, DSE had the highest CGI of 90.9
with NSE having the lowest CGI of 81.8%.
Figure 4.3 Corporate Governance Index per Country
Results in figure 4.3 indicate that CG score has been improving for the last five years
as indicated in Table 4.26. In 2009 the CGI score was 64.775% and in 2013 it
25%. The improvements in the score are brought about by the information a
awareness i.e. the companies are now more informed about CG.
. Further in 2011, DSE had the highest CGI of
with RSE having the lowest CGI of 67.3%. In
had 83.7% with
. In 2013, DSE had the highest CGI of 90.9%, USE
CG score has been improving for the last five years
the CGI score was 64.775% and in 2013 it
by the information a
144
Table 4.27: Capital structure, regulatory compliance and firm performance
Kenya
(NSE)
Tanzania
(DSE)
Uganda
(USE)
Rwanda
(RSE)
Mean SD Mean SD Mean SD Mean SD
Capital Structure
Leverage 0.324 0.021 0.225 0.012 0.422 0.042 0.314 0.043
Average score 0.475 0.031 0.376 0.022 0.238 0.048 0.454 0.041
Firm performance
Return on
Assets (ROA)
0.415 0.032 0.316 0.043 0.213 0.069 0.409 0.041
Tobin’s Q 1.489 0.452 1.384 0.553 1.683 0.759 1.472 0.448
Average score 0.952 0.242 0.850 0.298 0.948 0.414 0.941 0.245
Cost of capital
(COC)
0.082 0.003 0.073 0.004 0.181 0.013 0.039 0.021
Average score 0.082 0.003 0.073 0.004 0.181 0.013 0.039 0.021
Regulatory Compliance
Regulatory
Compliance
Index
0.570 0.0872 0.604 0.070 0.548 0.03604 0.505 0.0967
Average score 0.570 0.0872 0.604 0.070 0.548 0.03604 0.505 .0967
The study further compared the firms listed at the East African Community Securities
Exchange i.e. Kenya (NSE), Tanzania (DSE), Uganda (USE) and Rwanda (RSE) in terms
of their capital structure (leverage), regulatory compliance (corporate governance codes
and standards) and firm’s performance (Return on Assets (ROA), Tobin’s Q, Cost of
capital (COC), Cost of Equity (COE) and Cost of Debt (COD).
The study findings reveals that the overall average score for capital structure as far as
leverage and liquidity is concerned for NSE firms (Mean=0.475, SD=0.031), Tanzania
145
(Mean=0.376, SD=0.022), Uganda (Mean=0.238, SD=0.048) and Rwanda (Mean=0.454,
SD=0.041). As far as firm performance is concerned, Return on Assets (ROA) for Kenya
(NSE) (Mean=0.455, SD=0.105), Tanzania (DSE) (Mean=0.391, SD=0.129), Uganda
(USE) (Mean=1.288, SD=0.177), Rwanda (RSE) (Mean=0.440, SD=0.586). Further as
far as regulatory compliance is concerned, corporate governance codes and standards for
Kenya (NSE) (Mean=0.570, SD=0.0872), Tanzania (Mean=0.604, SD=0.070), Uganda
(mean=0.548, SD=0.036) and Rwanda (mean=0.505, SD=0.0967).
4.4 Correlation Analysis
Correlation analysis using Pearson product moment correlation coefficient technique was
used to establish the relationship between corporate governance index, capital structure,
rules and regulation and firm performance. The relevant results are as indicated.
Table 4.28: Correlation Analysis Results
*. Correlation is significant at the 0.05 level (2-tailed)
CG RC CS ROA Tobin Q COC
CG Pearson Correlation Sig. (2- tailed) N
1 0.000 280
RC Pearson Correlation Sig. (2- tailed) N
0.906 0.000 280
1 0.000 280
CS Pearson Correlation Sig. (2- tailed) N
-0.081 0.040 280
-0.130 0.030 280
1 0.000 280
ROA Pearson Correlation Sig. (2- tailed) N
0.782 0.00 280
0.746 0.000 280
-0.129 0.031 280
1 0.000 280
TOBIN Q
Pearson Correlation Sig. (2- tailed) N
0.523 0.000 280
0.535 0.000 280
-0.256 0.000 280
0.545 0.000 280
1 0.000 280
COC Pearson Correlation Sig. (2- tailed) N
-0.3357 0.000 280
-0.364 0.000 280
-0.104 0.000 280
-0.228 0.000 280
-0.174 0.004 280
1 0.000 280
146
The results in Table 4.28 indicate that the relationship between CG and RC is strong,
positive and statistically significant (r=.906, p-value=.000). Similarly, the relationship
between CG and ROA is strong, positive and statistically significant (r=.782, p-
value=.000. However the relationship between RC and COC is negative but moderately
significant as indicated by Pearson correlation coefficient of -.364 and p-value=000. This
implies that the study variables considered i.e. corporate governance index, capital
structure and rules and regulations play a critical role of influencing firm performance of
firms listed at the East African Community Security Exchanges.
147
CHAPTER FIVE
DISCUSSION OF FINDINGS
5.1 Introduction
The chapter presents the tests of hypotheses and the discussion of the research findings.
The six hypotheses of the study were tested using simple and multiple regressions.
Correlations were also conducted between various study variables. Tests of normality,
multicollinearity and homogeneity of variances were carried out. The study sought to
establish the effect of CG on firm performance and the influence of capital structure and
regulatory compliance on this effect. The tests were carried out using simple regression
analysis, multiple regression analysis, correlation analysis and stepwise regression
analysis. The tests were done at 5% significance level (α = 0.05). The evaluation focused
on the hypotheses derived from the objectives of the study.
5.2 Corporate Governance and Firm performance
The first objective of this study was to examine how CG affects firm performance among
the listed companies in EAC securities exchanges. The influence of CG was evaluated
based on dimensions of board structure and composition, ownership and shareholding,
transparency, disclosures and auditing, board remuneration and corporate ethics. These
were evaluated against the indicators of firm performance in order to test the influence on
dimensions, various regressions were done to find out if the combined effects were
sufficient or not to support the hypothesis. The influence of CG on firm performance was
measured by using ROA, Tobin Q and COC. The indicators were calculated based on
information from the financial statements from the listed companies. Thus, the first
hypothesis stated in the null form is as follows:
148
H1a: There is no significant relationship between CG and ROA among the listed
companies at the EAC securities exchanges
Hypothesis 1a sought to establish the influence of CG on firm performance. This
hypothesis was tested by regressing CG and firm performance guided by the equation
Y= β0+β1X
Where X represented CG and Y denoted ROA. The results of the regression are
presented in table 5.29 below.
Table 5.29: Effect of corporate governance on ROA
Model Summaryb Model R R Square Adjusted R
Square Std. Error of the Estimate
Durbin-Watson
1 .782a .611 .610 .1047843 1.597 a. Predictors: (Constant), CGI b. Dependent Variable: ROA
Coefficientsa Model Unstandardized Coefficients Standardized
Coefficients t Sig.
B Std. Error Beta
1 (Constant) -.703 .044 -16.015 .000 CGI 1.249 .060 .782 20.901 .000
a. Dependent Variable: ROA ANOVA a
Model Sum of Squares
Df Mean Square F Sig.
1 Regression 4.797 1 4.797 436.858 .000b Residual 3.052 278 .011 Total 7.849 279
a. Dependent Variable: ROA b. Predictors: (Constant), CGI
Residuals Statisticsa Minimum Maximum Mean Std. Deviation N Predicted Value -.028314 .421485 .205132 .1311186 280 Residual -.4120858 .2454981 0E-7 .1045964 280 Std. Predicted Value -1.780 1.650 .000 1.000 280 Std. Residual -3.933 2.343 .000 .998 280 a. Dependent Variable: ROA
149
The results presented in table 5.29 show that the influence of CG and ROA was
significant (R=.782). This was an indication that corporate governance dimensions
explained 61.1% (R2 =.611) of ROA. The other variables in the firms explained the
remaining 38.96%. The analysis from the model had the F value of 436.8. At p-value less
than 0.05, the findings thus were sufficient to support influence of CG dimensions,
implying that CG had statistically significant effects on firm performance. The hypothesis
that there is no significant relationship between CG and firm performance was therefore
not confirmed for ROA.
The results indicate that there is a positive significant relationship between CG and firm
performance as measured by ROA. The listed companies with high CGI score tended to
have higher performance. The results were consistent with the study conducted by
Shleifer and Vishny (1997) who reported that there is a positive relation between
ownership concentration and firm performance. It is confirmed further by (Ashbaugh et
al., 2004) who found a positive relationship between CG and firm performance as
measured by COC.
H1b: There is no significant relationship between CG and Tobin Q among the listed
companies at the EAC securities exchanges
Hypothesis 1b sought to establish the influence of corporate governance on firm
performance. This hypothesis was tested by regressing corporate governance and firm
performance guided by the equation Y= β0+β1X
Where X represented corporate governance and Y denoted Tobin Q. The results of the
regression are presented in table 5.30 below.
150
Table 5.30: Effect of corporate governance index on Tobin’s Q Model Summaryb
Model R R Square Adjusted R Square
Std. Error of the Estimate
Durbin-Watson
1 .523a .274 .271 .6559894 1.632 a. Predictors: (Constant), CGI b. Dependent Variable: TOBIN Q
ANOVA a Model Sum of
Squares Df Mean Square F Sig.
1 Regression 45.148 1 45.148 104.917 .000b Residual 119.630 278 .430 Total 164.778 279
a. Dependent Variable: TOBIN Q b. Predictors: (Constant), CGI
Coefficientsa Model Unstandardized Coefficients Standardized
Coefficients t Sig.
B Std. Error Beta
1 (Constant) -1.452 .275 -5.282 .000 CGI 3.833 .374 .523 10.243 .000
a. Dependent Variable: TOBIN Q Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N Predicted Value .618324 1.998303 1.334533 .4022700 280 Residual -1.3538210 2.9739790 0E-7 .6548128 280 Std. Predicted Value -1.780 1.650 .000 1.000 280 Std. Residual -2.064 4.534 .000 .998 280
The results of analysis to establish the effect of corporate governance index dimensions
on Tobin’s Q are shown in Table 5.30. Results of the study showed a relatively weak
relationship (R=.523) an indication that corporate governance index dimensions
explained 27.4% (R2 =.274) of Tobin’s Q with the remaining 72.6% explained by other
variables. The F value for the model was 104.917 at p-value greater than 0.05 (p>0.5), the
findings thus were sufficient to support the corporate governance index dimensions,
implying that corporate governance index dimensions had statistically insignificant
effects on Tobin’s Q. The hypothesis that there is no significant relationship between CG
151
and firm performance was therefore not confirmed for Tobin Q as a performance
indicator.
The results indicate that there is a positive significant relationship between CG and firm
performance as measured by Tobin’s Q. The results were consistent with the study
conducted by Gompers et al. (2003) who evaluated and found that there is a significant
relation between the governance index and Tobin’s Q. Where the index comprised a
broad spectrum of internal and external CG mechanisms and the study indicates that
firms with robust governance mechanisms are well managed and are profitable. The
findings also supported the study by Brown and Caylor (2006) who reported that there is
a positive association between Gov-score and Tobin’s Q.
H1c: There is no significant relationship between CG and COC among the listed
companies at the EAC securities exchanges
Hypothesis 1c sought to establish the influence of corporate governance on firm
performance. This hypothesis was tested by regressing corporate governance and firm
performance guided by the equation Y= β0+β1X
Where X represented corporate governance and Y denoted cost of capital. The results of
the regression are presented in table 5.31 below.
152
Table 5.31: Effect of corporate governance on Cost of capital Model Summaryb
Model R R Square Adjusted R Square
Std. Error of the Estimate
Durbin-Watson
1 .335a .112 .109 .0404066 1.700 a. Predictors: (Constant), CGI b. Dependent Variable: COC = COST OF CAPITAL
ANOVA a Model Sum of
Squares Df Mean Square F Sig.
1
Regression .057 1 .057 35.156 .000b
Residual .454 278 .002
Total .511 279
a. Dependent Variable: COC = COST OF CAPITAL b. Predictors: (Constant), CGI
Coefficientsa Model Unstandardized Coefficients Standardized
Coefficients t Sig.
B Std. Error Beta
1 (Constant) .150 .017 8.876 .000
CGI -.137 .023 -.335 -5.929 .000
a. Dependent Variable: COC = COST OF CAPITAL Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N Predicted Value .027247 .076451 .050914 .0143433 280 Residual -.0629613 .2577087 0E-7 .0403341 280 Std. Predicted Value -1.650 1.780 .000 1.000 280 Std. Residual -1.558 6.378 .000 .998 280 a. Dependent Variable: COC = COST OF CAPITAL
The results of analysis to establish the effect of CG index dimensions on cost of capital
are shown in Table 5.31. The study observed that the results had a relatively moderate or
average relationship (R=.335). This was an indication that CG index dimensions
explained 11.2% (R2 =.112) of cost of capital. The other variables explained the
remaining 88.8%. The analysis from the model had the F value of 35.156 at p-value less
than 0.05; the findings thus were insufficient to support the CG index dimensions,
implying that corporate governance index had statistically significant effects on COC.
153
The hypothesis that there is no significant relationship between CG and firm performance
as measured by COC was not confirmed.
The results indicate that there is a negative significant relationship between CG and firm
performance as measured by COC. The results indicates that as the debt equity ratio
increases firm performance decreases and this is consistent with the study of Ashbaugh et
al. (2004) who documented that there is a negative relationship between CG and COC as
measured by COE. Although COC is primarily a risk measure, it is also related to firm
value and can be considered a key determinant of firm’s value other than market and
accounting performance measures. Robust CG mechanisms will lead to lower firm risk
and subsequently to a lower COC, which implicitly increases a firm’s market value.
5.3 Corporate Governance and Capital Structure
The second objective of this study was to assess the relationship between CG and capital
structure among the listed companies in EAC securities exchanges. The influence of
corporate governance was evaluated based on certain dimensions (board structure and
composition, ownership and shareholding, transparency, disclosures and auditing, board
remuneration and corporate ethics). These were evaluated against the indicators of capital
structure. To test the influence on dimensions, various regressions were done to find out
if the combined effects were sufficient or not to support the hypotheses. Thus, the second
hypothesis stated in the null form is as follows:
154
H2: There is no significant relationship between corporate governance and capital
structure
Hypothesis 2 sought to establish the relationship between corporate governance and
capital structure. This hypothesis was tested by regressing corporate governance and
capital structure guided by the equation Y= β0+β1X
Where X represented corporate governance and Y denoted capital structure. The results
of the regression are presented in table 5.32 below.
Table 5.32: Relationship between corporate governance and capital structure Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate 1 .600a .360 .292 .53541
a. Predictors: (Constant), board structure and composition, ownership and shareholding, transparency, disclosures and auditing, board remuneration and corporate ethics
ANOVA a Model Sum of Squares df Mean Square F Sig.
1 Regression 9.173 1 1.529 5.333 .000b Residual 16.340 278 .287 Total 25.513 279
a. Dependent Variable: capital structure b. Predictors: (Constant), board structure and composition, ownership and shareholding, transparency, disclosures and auditing, board remuneration and corporate ethics
Coefficientsa Model Un-standardized
Coefficients Standardized Coefficients
B Std Error Beta t-value
Significance p-value
(Constant) .328 .117 3.030 .051
Corporate governance
.623
.111
.654
4.564
.000
a. Dependent Variable: capital structure b. Predictors: (Constant), board structure and composition, ownership and shareholding, transparency, disclosures and auditing, board remuneration and corporate ethics
155
The study observed that the results had a relationship between CG and capital structure
(R=.600). This was an indication that corporate governance explained 36.0% (R2 = .360)
of capital structure. The other variables affecting capital structure explained the
remaining 64.0%. The analysis from the model had the F value of 5.333at p-value <0.05,
the findings were sufficient to support the relationship between corporate governance and
capital structure, implying that corporate governance had statistically significant effects
on capital structure.
The results indicate that there is a positive significant relationship between CG and
capital structure. The debt/equity ratio increases as CG increases. Although in the
literature there are varied results but the study is consistent with the study by Berger and
Lubrano (2006) who found that firms with larger boards that is weak CG tend to have
higher leverage. Their result suggest that large board as proxy for CG which are more
entrenched due to superior monitoring by regulatory bodies pursue higher leverage to
raise company value.
5.4 Capital Structure and Firm Performance
The third objective of this study was to assess the relationship between capital structure
and firm performance among the listed companies in EAC securities exchanges. The
influence of capital structure was evaluated based on leverage and liquidity while firm
performance was evaluated by considering the composite of ROA, Tobin Q and cost of
capital (COC). To test the influence on dimensions, various regressions were done to find
out if the combined effects were sufficient or not to support the hypotheses. Thus, the
third hypothesis stated in the null form is as follows:
156
H3a: There is no significant relationship between capital structure and ROA among
the listed companies at the EAC securities exchanges
Hypothesis 3a sought to establish the influence of capital structure on firm performance.
This hypothesis was tested by regressing capital structure and firm performance guided
by the equation Y= β0+β1X
Where X represented capital structure and Y denoted ROA. The results of the regression
are presented in table 5.33 below.
Table 5.33: Effect of capital structure on ROA
Model Summary
Model R R Square Adjusted R Square Std. Error of the
Estimate
1 .416a .173 .157 .62228
a. Predictors: (Constant) Leverage
ANOVA b
Model Sum of Squares df Mean Square F Sig.
1 Regression 4.054 1 4.054 10.470 .002a
Residual 19.361 278 .387
Total 23.416 279
a. Predictors: (Constant) Leverage
b. Dependent Variable: Return on Assets Coefficients
Model
Unstandardized Coefficients Standardized Coefficients
T
Sig.
B Std. Error Beta (Constant) 1.996 .712 2.804 .007
Leverage .940 .256 .651 3.666 .001 a. Dependent Variable: Return on Assets
The results of analysis to establish the effects of capital structure dimensions on return on
assets are shown in Table 5.33. Results indicate relative relationship between capital
157
structure and ROA (R= .416). The results indicate that a relationship exists between
capital structure and ROA. Capital structure as a variable explained 17.3% (R2 =.173) of
return on assets with the remaining 82.7% explained by other variables. The
corresponding F value for the model was 10.470 at p-value greater than 0.05 (p<0.5),
hence implying that capital structure variable was statistically significant effects on return
on assets. The analysis of significance of capital structure dimensions on return on assets
is summarized in Table 5.33 above. The hypothesis that there is no significant
relationship between CG and ROA was therefore not confirmed.
The results indicate that there is a positive significant relationship between capital
structure and firm performance as measured by ROA. The results were consistent with
the study conducted by Pinegar and Wilbricht (1989), they argued that capital structure
can be used by increasing debt level without increasing agency costs and this will force
the managers to invest in profitable ventures that will benefit the shareholders, because if
they decide to invest in non-profitable ventures they will be unable to pay debt interest.
H3b: There is no significant relationship between capital structure and Tobin Q
among the listed companies at the EAC securities exchanges
Hypothesis 3b sought to establish the influence of capital structure on firm performance.
This hypothesis was tested by regressing capital structure and firm performance guided
by the equation Y= β0+β1X
Where X represented capital structure and Y denoted Tobin Q. The results of the
regression are presented in table 5.34 below.
158
Table 5.34: Effect of capital structure on Tobin Q
Model Summary
Model R R Square Adjusted R Square Std. Error of the
Estimate
1 .302a .091 .036 .64535
a. Predictors: (Constant), liquidity, Leverage
ANOVA a
Model Sum of Squares df Mean Square F Sig.
1
Regression 2.050 1 .683 1.641 .192b
Residual 20.407 278 .416
Total 22.457 279
a. Dependent Variable: Tobin’s Q
b. Predictors: (Constant)Leverage
Coefficients
Model
Unstandardized Coefficients Standardized
Coefficients
T
Sig.
B Std. Error Beta
(Constant) 2.471 .859 2.878 .006
Leverage 1.264 .303 .707 4.170 .000
The results of analysis to establish the effect of capital structure dimensions on Tobin’s Q
are shown in Table 5.34. The study observed that there is no significant relationship
between capital structure and firm performance as measured by Tobin’s Q, and it was
relatively weak relationship (R=.309). This was an indication that capital structure
dimensions explained 9.1% (R2 = 0.091 of Tobin’s Q. The other variables explained the
remaining 90.9%. The analysis from the model had the F value of 1.641at p-value>0.05,
the findings were not sufficient to support influence of capital structure dimensions,
implying that capital structure had statistically insignificant effects on Tobin’s Q. The
159
results show statistically insignificant results for liquidity and significant results for
leverage.
H3c: There is no significant relationship between capital structure and cost of
capital among the listed companies at the EAC securities exchanges
Hypothesis 3c sought to establish the influence of capital structure on firm performance.
This hypothesis was tested by regressing capital structure and firm performance guided
by the equation Y= β0+β1X
Where X represented capital structure and Y denoted cost of capital. The results of the
regression are presented in table 5.35 below.
Table 5.35: Effect of capital structure on cost of capital
Model Summary Model R R Square Adjusted R Square Std. Error of the
Estimate 1 .389a .152 .100 .83013 a. Predictors: (Constant) Leverage
ANOVA a Model Sum of Squares df
Mean Square
F
Sig.
1 Regression 6.035 1 2.012 2.919 .043b Residual 33.767 278 .689 Total 39.802 279
a. Dependent Variable: Cost of capital b. Predictors: (Constant) Leverage
Coefficients
Model Unstandardized Coefficients Standardized
Coefficients
T
Sig.
B Std. Error Beta
(Constant) 1.937 .751 2.580 .013 Leverage 1.253 .270 .757 4.637 .000
160
The results of analysis to establish the effect of capital structure dimensions on cost of
capital are shown in Table 5.35. The study observed that the results had a relatively weak
relationship (R=.389). This was an indication that capital structure dimensions explained
15.2% (R2 =.152) of cost of capital. The other variables explained the remaining 84.8%.
The analysis from the model had the F value of 7.642 at p-value<0.05, the findings were
sufficient to support influence of capital structure dimensions, implying that capital
structure had statistically significant effects on cost of capital. The hypothesis that there is
no significant relationship between CG and COC was therefore not confirmed.
5.5 Moderating Effect of Regulatory Compliance on firm Performance
This study sought to determine the influence of regulatory compliance on the relationship
between corporate governance and firm performance. To assess the moderating effect,
Hypothesis 4 was formulated in the null form as follows:
H4a: There is no significant effect of regulatory compliance on the relationship
between corporate governance and ROA
This involved testing the main effects of the independent variable (corporate governance)
and moderator variable (regulatory compliance) on the dependent variable (the firm
performance is measured by ROA) and the interaction between CG and the regulatory
compliance. The significance of the independent variable and the moderator variable is
not particularly relevant in determining moderation. Moderation is assumed to take place
if the interaction between CG and the regulatory compliance is significant. The Baron
and Kenny (1986) approach in testing for moderation was employed for the purposes of
this study guided by the equation:
161
Y= β0+β1X+ β2Z+ β3XZ
Where X= Independent variable (corporate governance)
Z= Moderator (regulatory compliance)
XZ= Product of the standardized scores for the independent variable and the
moderator
Y= ROA
A z –score specifies the precise location of each value within a distribution.
The sign of the z-score signifies whether the score is above the mean (positive) or below
the mean (negative). The numerical value of the z-score specifies the distance from the
mean by counting the number of standard deviations between X and µ.
The z –score is calculated as:
� �� � �
�
Z = the standardized score
X = the X value
To create an interaction term, corporate governance and the regulatory compliance
measures were first centred and a single item indicator representing the product of the
two measures calculated. The creation of a new variable by multiplying the scores of
corporate governance and the regulatory compliance factors risks creating a
multicollinearity problem. To address the multicollinearity problem, which can affect the
estimation of the regression coefficients for the main effects, the two factors were
converted to standardized (Z) scores that have mean zero and standard deviation one. The
two standardized variables (corporate governance and the regulatory compliance) were
162
then multiplied to create the interaction variable. The relevant analytical results are
portrayed in Table 5.36
Table 5.36: Regression results of the moderating effect of RC on the relationship
between CG and ROA
Coefficients Variables Model 1 Model 2 Model 3 CG .782(.000) .594(.000) .585(.000) RC - .208(.019) .202(.020) CG*RC - - .099(.008) R Square .611 .619 .628 Adjusted R Square .610 .616 .624 F Statistics 436.858 224.847 155.542 Significance .000 .000 .000 Df1 1 2 3 Df2 278 277 276
The results in Table 5.36 show that corporate governance and regulatory compliance
explained 62.8% of the variation in firm performance (R2=.628). Under change statistics,
the results reveal that the R2 change increased by 1.7% from .611 to .624 (R2
change=.017) when the interaction variable (corporate governance*regulatory
compliance) was added. The change was statistically significant at α=.05 (p-value=.000).
The results show a statistically significant relationship between corporate governance,
regulatory compliance and the interaction (F=155.542, p-value=.000).
The results in model 1, 2 and 3 show statistically significant regression coefficients for
corporate governance (β=.782, p-value=.000) indicating that there is a linear dependence
of ROA on corporate governance. On the other hand, there is a statistically significant
relationship between regulatory compliance and firm performance (ROA) (β=.208, p-
163
value=.019). Similarly, a statistically linear relationship of ROA on the multiplicative
term of corporate governance and regulatory compliance was detected (β=.099, p=.008).
This implies that changes in the regulatory compliance may positively affect corporate
governance and firm performance relationship as the direction of the relationship is
positive. The hypothesis that there is no significant moderating effect of regulatory
compliance on the relationship between CG and firm performance was therefore not
confirmed.
The results indicate that there is a significant positive moderating effect of regulatory
compliance on relationship between CG and firm performance as measured by ROA.
The results were consistent the literature reviewed, (Hermain, 2005) found that
regulations has a positive significant effect on the relationship between CG and firm
performance. Drobetz (2002) also stated that the existence of the agency problem
associated with the separation of owners and managers is mitigated by the regulations. In
different financial markets and countries, rules governing listed companies come from
different sources including the Company Act, security listing regulations, bankruptcy,
takeover, and competition laws and accounting standards. Research suggests that the
extent of regulatory compliance of listed companies in a country is an important
determinant of the development of financial markets (La Porta et al. 2000) and regulatory
compliance not only prevent expropriation by managers or controlling shareholders, it is
also central to understanding the diversity in CG.
164
H4b: There is no significant effect of regulatory compliance on the relationship
between corporate governance and Tobin Q
The second sub hypothesis tests the effects of CG and RC (moderator variable) on Tobin
Q. Moderation is assumed to take place if the interaction between CG and the regulatory
compliance is significant. The relevant analytical results are portrayed in Table 5.37
Table 5.37: Regression results of the moderating effect of RC on the relationship
between CG and Tobin Q
Coefficients Variables Model 1 Model 2 Model 3 CG .523(.000) .216(.071) .201(.087) RC - .339(.005) .329(.005) CG*RC - - .184(.000) R Square .274 .295 .328 Adjusted R Square .271 .289 .320 F Statistics 104.917 57.818 44.847 Significance .000 .000 .000 Df1 1 2 3 Df2 278 277 276
The results in Table 5.37 show that corporate governance and regulatory compliance
explained 32.8% of the variation in firm performance (R2=.328). Under change statistics,
the results reveal that the R2 change increased by 5.4% from .274 to .328 (R2
change=.054) when the interaction variable (corporate governance*regulatory
compliance) was added. The change was statistically insignificant at α=.05 (p-
value=.000). The results show a statistically insignificant relationship between corporate
governance, regulatory compliance and the interaction because in model 2 and 3 p-
value=.071 and .087 respectively.
165
The results in model 1, 2 and 3 show statistically insignificant regression coefficients for
corporate governance (β=.523, p-value=.071) indicating that there is a linear dependence
of Tobin Q on corporate governance. On the other hand, there is a statistically significant
relationship between regulatory compliance and firm performance (Tobin Q) (β=.339, p-
value=.005).
H4c: There is no significant effect of regulatory compliance on the relationship
between corporate governance and COC
The third sub hypothesis tests the effects of CG and RC (moderator variable) on COC.
Moderation is assumed to take place if the interaction between CG and the regulatory
compliance is significant. The relevant analytical results are portrayed in Table 5.38
Table 5.38: Regression results of the moderating effect of RC on the relationship
between CG and COC
Coefficients Variables Model 1 Model 2 Model 3 CG -.335(.000) -.027(.837) -.052(.679) RC - .340(.011) -.355(.005) CG*RC - - .290(.000) R Square .112 .133 .216 Adjusted R Square .109 .127 .207 F Statistics 35.156 21.229 25.286 Significance .000 .000 .000 Df1 1 2 3 Df2 278 277 276
The results in Table 5.38 show that corporate governance and regulatory compliance
explained 21.6% of the variation in firm performance (R2=.216). Under change statistics,
the results reveal that the R2 change increased by 10.4% from .112 to .216 (R2
166
change=.104) when the interaction variable (corporate governance*regulatory
compliance) was added. The change was statistically insignificant at α=.05 (p-
value=.000). The results show a statistically insignificant relationship between corporate
governance, regulatory compliance and the interaction because in model 2 and 3 p-
value=.837 and .679 respectively.
The results in model 1, 2 and 3 show statistically insignificant regression coefficients for
corporate governance (β=-.027, p-value=.837) indicating that there is a negative linear
dependence of COC on corporate governance.
5.6 Intervening effect of capital structure on the relationship between corporate
governance and firm Performance
The firth objective of the study sought to establish whether there is a significant
intervening effect of capital structure on the relationship between corporate governance
and firm performance. The hypothesis is divided into three sub hypothesis to consider the
individual effects of firm performance as measured by ROA, Tobin Q and COC. Thus,
the firth hypothesis stated in the null form is as follows:
H5a: There is no significant intervening effect of capital structure on the
relationship between corporate governance and ROA
First, ROA was regressed on corporate governance and the standardized regression
coefficients (beta) examined to determine the size and direction of the relationship and
whether it was statistically significant. If this relationship is not statistically significant,
there can be no intervened effect. The pertinent results are summarized in Table 5.39
167
Secondly, a regression analysis was performed and the betas examined for the strength,
direction and significance of the relationship. In step one, firm performance was
regressed on the capital structure and in step two, and firm performance was regressed on
corporate governance to assess if there was a significant change. When controlling for the
effects of the capital structure on firm performance, the effect of the corporate
governance on the firm performance should no longer be statistically significant at α=.05.
The relevant results are summarized in Table 5.39
Table 5.39: Regression results of ROA on capital structure and corporate governance Coefficients Variables Model 1 Model 2 Model 3 CG .782(.000) .776(.000) .770(.000) CS - -.066(.050) -.058(.115) CG*CS - - -.108(.004) R Square .611 .615 .627 Adjusted R Square .610 .613 .623 F Statistics 436.858 221.696 154.708 Significance .000 .000 .000 Df1 1 2 3 Df2 278 277 276
The results in Table 5.39 show that capital structure explain 62.7% of the variation in
firm performance (R2 =.627). At step 2, corporate governance, adds to the ROA as the
variation increased from .611 to .627 (R2 change=.627 p-value=.000). The results reveal
that the variance explained by capital structure is significant (p-value=.050) for CS. The
results revealed that the regression coefficients for corporate governance decreased from
β=.782, p-value=.000 to β=.770, p-value=.000 when capital structure were added to the
regression.
The hypothesis that there is no significant intervening effect of capital structure on the
relationship between CG and firm performance was therefore not confirmed. The results
168
indicate that there is an insignificant intervening effect of capital structure on the
relationship between CG and firm performance as measured by ROA.
H5b: There is no significant intervening effect of capital structure on the
relationship between corporate governance and Tobin Q
Tobin Q was regressed on corporate governance and the standardized regression
coefficients (beta) examined to determine the size and direction of the relationship and
whether it was statistically significant. If this relationship is not statistically significant,
there can be no intervened effect. The pertinent results are summarized in Table 5.40
Secondly, a regression analysis was performed and the betas examined for the strength,
direction and significance of the relationship. In step one, Tobin Q was regressed on the
capital structure and in step two, and Tobin Q was regressed on corporate governance to
assess if there was a significant change. When controlling for the effects of the capital
structure on Tobin Q, the effect of the corporate governance on Tobin Q is summarized in
Table 5.40
Table 5.40: Regression results of Tobin Q on capital structure and corporate governance Coefficients Variables Model 1 Model 2 Model 3 CG .523(.000) .506(.000) .499(.000) CS - -.215(.000) -.206(.000) CG*CS - - -.124(.013) R Square .274 .320 .335 Adjusted R Square .271 .315 .328 F Statistics 104.917 65.166 46.377 Significance .000 .000 .000 Df1 1 2 3 Df2 278 277 276
169
The results in Table 5.40 show that capital structure explain 33.5% of the variation in
firm performance (R2 =.335). At step 2, corporate governance, adds to the Tobin Q as the
variation increased from .274 to .335 (R2 change=.015 p-value=.000). The results reveal
that the variance explained by capital structure is significant (p-value=.013) for CS. The
results revealed that the regression coefficients for corporate governance decreased
slightly from β=.523, p-value=.000 to β=.499, p-value=.000 when capital structure were
added to the regression.
The hypothesis that there is no significant intervening effect of capital structure on the
relationship between CG and firm performance was therefore not confirmed. The results
indicate that there is a significant intervening effect of capital structure on the
relationship between CG and firm performance as measured by Tobin Q. The results
were consistent the literature, (William, 1988) while referring to the analysis done by
Jensen and Meckling (1976) stated that capital structure has an influence on the relation
between CG and firm performance.
H5c: There is no significant intervening effect of capital structure on the
relationship between corporate governance and COC.
COC was regressed on corporate governance and capital structure, and the standardized
regression coefficients examined. The betas were examined for the strength, direction and
significance of the relationship. The effect of the corporate governance on Tobin Q is
summarized in Table 5.41
170
Table 5.41: Regression results of COC on capital structure and corporate governance Coefficients Variables Model 1 Model 2 Model 3 CG -.335(.000) -.346(.000) -.345(.000) CS - -.132(.000) -.133(.019) CG*CS - - -.016(.775) R Square .112 .130 .130 Adjusted R Square .109 .123 .120 F Statistics 35.156 20.608 13.720 Significance .000 .000 .000 Df1 1 2 3 Df2 278 277 276
Results in Table 5.41 indicates that capital structure explained only 13% of the variation
in firm performance as measured by COC (R2 =.130). The results reveal that the variance
explained by capital structure is insignificant (p-value=.775) for CS. The results revealed
that the regression coefficients for corporate governance decreased slightly from β=.335,
p-value=.000 to β=.345, p-value=.000 when capital structure were added to the
regression. The hypothesis that there is no significant intervening effect of capital
structure on the relationship between CG and firm performance as measured by COC was
therefore confirmed.
5.7 Joint effect of capital structure and regulatory compliance on the relationship
between corporate governance and firm Performance.
The aim of objective six of the study was to establish the joint effect of capital structure
and regulatory compliance on the relationship between corporate governance and firm
performance. The sixth hypothesis is further sub divided into three sub hypothesis to
consider the effects of ROA, Tobin Q and COC. Thus, the sixth hypothesis stated in the
null form is as follows:
171
H6a: There is no significant joint effect of capital structure and regulatory
compliance on the relationship between corporate governance and ROA
Step wise regression analysis was carried out guided by the equation:
Y= β0 + β1X1 + β2X2 + β3X3 + β4 X 4
Where X 1 =corporate governance
X 2 = capital structure X 3 = regulatory compliance β = Coefficient of variation Y=
ROA. The results from the regression analysis were as presented in table 5.42 below:
Table 5.42: Regression results of the independent, intervening and moderating variable on ROA Coefficients Variables Model 1 Model 2 Model 3 CG .782(.000) .594(.000) .624(.000) CS - .208(.000) .195(.026) CG*CS*RC - - -.082(.031) R Square .611 .619 .625 Adjusted R Square .610 .616 .621 F Statistics 436.858 224.847 153.447 Significance .000 .000 .000 Df1 1 2 3 Df2 278 277 276
The results in Table 5.42 reveal that the joint effect of corporate governance, capital
structure, regulatory compliance explain 62.5% of the variation in ROA (R2=.625). In the
model 1 the variations are explained by 61.1% (R2=.611), in model 2 the variations are
explained by 61.9% (R2=.619) while in model 3 the variations are explained by 62.5%
(R2=.625) which means as regulatory compliance is added to the regression equation the
variations increases from 61.1% to 62.5%. The results show that the joint effect of the
study variables are statistically significant (β=-.082, p-value=.031). This implies that the
study variables jointly predict firm performance (ROA) at the EAC securities exchange.
172
H6b: There is no significant joint effect of capital structure and regulatory
compliance on the relationship between corporate governance and Tobin Q
Step wise regression analysis was carried out guided by the equation:
Y= β0 + β1X1 + β2X2 + β3X3 + β4 X 4
Where X 1 =corporate governance
X 2 = capital structure X 3 = regulatory compliance β = Coefficient of variation Y=
Tobin Q. The results from the regression analysis were as presented in table 5.43 below:
Table 5.43: Regression results of the independent, intervening and moderating variable on Tobin Q Coefficients Variables Model 1 Model 2 Model 3 CG .535(.000) .572(.000) .304(.000) CS - -.206(.000) -.227(.000) CG*CS*RC - - -.300(.011) R Square .286 .327 .343 Adjusted R Square .284 .322 .336 F Statistics 111.428 67.387 48.036 Significance .000 .000 .000 Df1 1 2 3 Df2 278 277 276
Table 5.43 above indicates that there is a joint effect of capital structure and regulatory
compliance on the relationship between corporate governance and firm performance as
measured by Tobin Q. The study results reveal that the joint effect of corporate
governance, capital structure, regulatory compliance explain 34.4% of the variation in
Tobin Q (R2=.343). In the model 1 the variations are explained by 28.6% (R2=.286) , in
model 2 the variations are explained by 32.7% (R2=.327) while in model 3 the variations
are explained by 34.3% (R2=.343) which means as capital structure and regulatory
compliance are added to the regression equation the variations increases from 28.6% to
34.3%. The results show that the joint effect of the study variables are statistically
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significant (β=.300, p-value=.011). This implies that the study variables jointly predict
firm performance as measured by Tobin Q at the EAC securities exchange.
H6c: There is no significant joint effect of capital structure and regulatory
compliance on the relationship between corporate governance and COC
Step wise regression analysis was carried out guided by the equation:
Y= β0 + β1X1 + β2X2 + β3X3 + β4 X 4
Where X 1 =corporate governance
X 2 = capital structure X 3 = regulatory compliance β = Coefficient of variation Y=
COC. The results from the regression analysis were as presented in table 5.44 below:
Table 5.44: Regression results of the independent, intervening and moderating variable on COC Coefficients Variables Model 1 Model 2 RC -.364(.000) -.384(.000) RC*CS - -.154(.006) R Square .133 .156 Adjusted R Square .130 .150 F Statistics 42.562 7.633 Significance .000 .000 Df1 1 2 Df2 278 277
Table 5.44 above indicates that there is no joint effect of capital structure and regulatory
compliance on the relationship between corporate governance and firm performance as
measured by COC. The results indicate that regulatory compliance and capital structure
only explain 15% (R2=.150) of the variations in COC. In the model 1 the variations are
explained by 13.0% (R2=.130) and in model 2 the variations are explained by 15.0%
(R2=.15).
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5.8 Discussion of the hypotheses tests and research findings
5.8.1 The influence of CG on firm performance
The first objective of the study was to establish the influence of corporate governance on
firm performance of listed companies at the East African securities exchange. This was
achieved by analysing the financial statements of the quoted companies. The corporate
governance was sub-divided into five sub-indices i.e. board structure and composition,
ownership and shareholding, transparency, disclosures and auditing, board remuneration
and corporate ethics. The results of the correlation show that there is a significant positive
relationship between CG characteristics and firm performance of listed companies. The
results evidenced a statistically significant influence of CG on firm performance in so far
as ROA, Tobin Q and cost of capital. Hypothesis (H1) was therefore not confirmed by
the study. The results indicated that good CG influences firm performance, therefore it
can be concluded that higher profitability for firms listed at East African securities
exchange is due to better CG practices.
The above results were supported by prior research on the relationship between CG and
firm performance. The results were consistent with the study conducted by Shleifer and
Vishny (1997) who reported that there is a positive relation between ownership
concentration and firm performance. It is confirmed further by (Ashbaugh et al., 2004)
who found a positive relationship between CG and firm performance as measured by
COC. However, other scholars have different views on the relationship between CG and
firm performance. Cremers and Ferrell (2009) examined the effects of corporate
governance on the firm‘s operational performance and found a negative association
between corporate governance and firm performance. Hermalin and Weisbach (1996) on
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the other hand evaluated the effects of board composition and effects of direct incentives
on firm performance and found no relationship. Daily and Dalton (1992) used both
accounting based measures and market based performance measures and they found no
association between CG and financial performance.
During past decades, scholars designed CG mechanisms to discipline managers through
monitoring and advising by the board of directors, because managers are self-interested,
risk averse and pursue their own goals that may diverge from those of the shareholders.
Therefore CG should effectively improve the firm performance (Pham et al., 2007).
Specifically, scholars have provided explanations for the positive effect of corporate
governance on firm performance. For example, some scholars have found that corporate
governance can increase the managerial efficiency of capital and then improve the
performance of firms. Shleifer and Vishny (1997) indicated that a firm with effective CG
can invest in profitable projects and then increase the efficiency of operation and higher
cash flow.
The results about the significance of the relationship between CG and firm performance
in East Africa securities exchange based on ROA, Tobin Q and COC are supported by
agency theory. According to the literature, the relationship between CG and firm
performance is grounded on agency theory, which is concerned with aligning the interest
of shareholders and managers to maximize the wealth of the company. Therefore,
advocates of agency theory argue that the position of CEO and the chairman should be
separated, as the combined structure can reduce the effectiveness of monitoring
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(Donaldson 1990). In support of the agency theory, the separation of the two roles has
been adopted by companies around the world (Banks 2004).
The results also revealed an increase in firm performance for companies for the period
under review. Therefore, the main purpose of the CG mechanism is to provide
reassurance to shareholders that managers will achieve results which are in the best
interest of the shareholders (Shleifer & Vishny 1997). One way in which this can be
achieved is through an effectively structured board that ensures the interests of the
managers are in line with those of the shareholders. The practice of separation of the
leadership roles is becoming increasingly common among listed companies in the East
Africa securities exchange.
The results of this study also indicated that boards dominated by NEDs are significantly
related to performance for both accounting-based measures and market- based measures.
This implies that the companies that complied with the recommendations of code of best
practice on corporate governance performed well. The Cadbury Report (1992), Hampel
Report (1998) and OECD principles recommended that boards comprised of a majority of
non-executive directors. The CMA listing requirements in the East Africa community
exchanges have also incorporated the above principles in their governance practices,
NEDs bring independence of mind and judgment on issues of strategy and governance on
running the business, and also see themselves as assisting in enhancing prosperity of the
companies and play an important part in improving the performance of the business
(Cadbury 2002). The results also imply that to be effect , a board must have the right mix
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of skills and experience and work together as a team, which will encourage diverse and
healthy debate in the interest of the investors and the company (Roche 2005 ).
5.8.2 The effect of CG on capital structure
The second objective of the study was to establish the relationship between CG and
capital structure. On the basis of this objective, the study hypothesized that there is no
relationship between CG and capital structure. The assessment of CG and capital
structure was done by reviewing the financial statements of companies listed at the East
Africa community security exchanges. The hypothesis that there is no relationship
between CG and firm performance was therefore not confirmed. These results are in line
with existing literature which links CG and capital structure.
The study indicates that CG is positively correlated to capital structure. Capital structure
as measured by leverage shows the relationship between long term liabilities and
shareholder’s equity and it can be a powerful tool to implement CG. According to CG
principles shareholders equity should be greater than the long term liabilities to create
value (Lipton and Lorsch, 1992). The correlation coefficient between CG and capital
structure was a positive correlation (β=.623). The study results are supported by literature
although there are varied results. Berger and Lubrano (2006) found that firms with larger
board membership have lower leverage or debt ratio and they assumed that larger board’s
size translates into strong pressure from the corporate board to make managers pursue
lower leverage due to superior monitoring. The results were also supported by Berger et
al., 1997 who stated that firms with higher leverage rather have relatively more outside
directors. According to Abor (2007) there exist a significant negative relationship
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between CEO duality and leverage where it implies that larger boards adopt low debt
policy. The second hypothesis (H2) was to test whether there is no significant
relationship between CG and capital structure is. H2 was rejected in that there was a
significant positive relationship between CG and capital structure (Table 6.37)
5.8.3 The effect of capital structure on firm performance
The third objective of the study was to determine the relationship between capital
structure and firm performance of listed companies at the East African securities
exchange. The firm performance was measured by ROA, Tobin Q and COC, and the test
results were varied. The study results indicated that there is a positive significant
relationship between capital structure and firm performance for all the three indicators of
measurements used in the study. The hypothesis that there is no relationship between
capital structure and firm performance was therefore not confirmed. These results are in
line with existing literature which links capital structure and firm performance.
The literature reviewed indicated that there are positive and negative significant
relationship between capital structure and firm performance. The study findings is
supported by Harris and Raviv (1991) and Stulz (2004) who stated that there is a positive
significant relationship between capital structure firm performance. There are also other
studies who found a negative significant relationship. Jensen and Meckling (1976) found
that there is a negative significant relationship between capital structure and performance
which is associated with growth opportunities, interest coverage and probability of
reorganization following default. There are also earlier studies by Modigliani and Miller
(1958) which pointed out that capital structure is irrelevant i.e. Leverage has no
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significant relationship with firm value which depends only on the assets held by the
firm. The third hypothesis (H3) is therefore rejected in that there is a positive significant
relation between capital structure and firm performance.
5.8.4 The moderating effect of regulatory compliance on the relationship between
CG and firm performance
The fourth objective of the study was to establish the moderating effect of regulatory
compliance on the relationship between CG and firm performance. The Baron and Kenny
(1986) approach was used to test the hypothesis that there is no significant moderating
effect on the relationship between CG and firm performance. The results yielded a
significant interaction between CG, regulatory compliance and firm performance as
measured by ROA. The hypothesis that there no influence of CG on firm performance as
moderated by regulatory compliance was therefore not confirmed. There is minimal
literature that attempts to link CG, regulatory compliance. However studies have been
done linking CG practices to firm performance.
In different financial markets and countries, rules governing listed companies come from
different sources including the Company Act, security listing regulations, bankruptcy,
takeover, and competition laws and accounting standards. Research suggests that the
extent of regulatory compliance of listed companies in a country is an important
determinant of the development of financial markets. La Porta et al. (2000) found out that
regulatory compliance not only prevent expropriation by managers or controlling
shareholders, it is also central to understanding the diversity in ownership structure,
corporate governance, breadth and depth of capital markets, and the efficiency of
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investment allocation. La Porta et al. (2000) however noted that reforming or improving
regulatory compliance is a difficult task as the legal structure of a country is deeply
rooted and in view of the existing entrenched economic interests.
The researcher further tested for mediation by exploring the possibility of a mediating
effect of regulatory compliance in the influence of CG on firm performance. The results
provided sufficient statistical evidence to signify a mediation relationship. This implies
that regulatory compliance, CG and firm performance do have a direct relationship, and
that the interaction of regulatory compliance and CG increases the influence on firm
performance. La Porta et al. (2002) found evidence of higher valuation, measured by
Tobin’s Q, of firms in wealthy countries with better regulatory compliance. This evidence
indirectly supports the effects of regulatory compliance by companies in many countries.
The differences in structure of law and enforcement among various countries in area of
historical trend of their laws, level of corruption, quality of their enforcement determines
the different level of regulatory compliance.
5.8.5 The intervening effect of capital structure on the relationship between CG and
firm performance
Objective five sought to establish whether capital structure was intervening on the effect
of CG on firm performance. The Baron and Kenny (1986) approach was used to test the
hypothesis that there is no significant intervening effect of capital structure on the
relationship between CG and firm performance. The results yielded a significant
intervening effect between CG, capital structure and firm performance as measured by
ROA, Tobin Q and COC. The hypothesis that there is no significant intervening effect of
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capital structure on the relationship between CG and firm performance was therefore not
confirmed. Firm performance is enhanced when there is good CG which will also
influence the capital structure of the listed companies.
There is empirical evidence that the firm performance depends on CG and capital
structure decisions. The agency theory suggest that CG together with capital structure
decisions influences firm performance, in that it mitigates agency conflicts between
managers, shareholders and debt holders (Putnan ,1993). The firm’s financial choice that
alters ownership assets modifies the importance and the intensity of some of the primary
stakeholders’ interest in firm governance. Capital structure can be analysed not only in
purely financial terms it can also be analysed by looking at the rights and attributes that
characterise the firm’s assets and that influence, with different levels of governance
activities. Equity and debt, therefore, must be considered as both financial instruments
and CG instruments: debt subordinates governance activities to stricter management,
while equity allows for greater flexibility and decision making power. Jensen and
Meckling (1976), by making a distinction between internal and external equity,
contextualize the relation between ownership and capital structures. It can thus be
inferred that when capital structure becomes an instrument of CG, not only the mix
between debt and equity but how to make decisions and manage the firm must be dealt
with (Zingales, 2000).
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5.8.6 Joint effect of capital structure and regulatory compliance on the relationship
between CG and firm performance
Objective six sought to establish the joint effect of capital structure and regulatory
compliance on the relationship between CG and firm performance.
Stepwise regression analysis was carried out guided by the equation:
Y= β0 + β1X1 + β2X2 + β3X3 + β4 X 4
Regulatory compliance contributed more in explaining the influence of CG on firm
performance than all other variables. Capital structure was the least contributor. The
overall model remained largely significant on every addition of variables. This gave an
indication of regulatory compliance and capital structure having a direct interaction with
CG when explaining influence firm performance.
The influence of CG on firm performance was evaluated in hypothesis one and about
61.1% of the variation in ROA as a financial measure was explained was explained by
variation in CG, 27.4% of variations in Tobin Q was explained by variations in CG and
11.2% of the variations in COC was explained by variations in CG. The influence of
capital structure on firm performance was evaluated in hypothesis three and the results
indicated that 17.3% of the variation in ROA was explained by variation in capital
structure, 9.1% of the variations in Tobin Q and 15.2% variations in COC were explained
by variations in capital structure respectively. The joint effect of CG, capital structure,
regulatory compliance and firm performance evaluated in hypothesis six indicated that
62.5% of the variation in firm performance (ROA) was explained in the model. Although
the influence in joint effect is not a direct one, there was evidence that the three variables
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(CG, capital structure, regulatory compliance) in combination increased the explained
variation in firm performance and this was evidence that they each had a contribution to
firm performance. The joint effect of CG, capital structure and regulatory compliance on
firm performance as evidenced in the model was greater than the individual effects of
CG, capital structure and regulatory compliance firm performance, thus not confirming
hypothesis six.
The results support the study by Anderson and Gupta (2009) who found that there is joint
effect of a country’s financial structure and legal system does matter when explaining the
relationship between firm specific performance and the firm’s overall level of
governance. The results also suggest that firms operating in the market combination
countries tend to exhibit better CG as measured by corporate governance quotient.
5.9 Summary of Research Findings
Chapter five presented hypotheses testing as well as discussions of the findings of the
study. The hypotheses were stated null hypotheses form and were tested using correlation
and regression analysis. Based on the results, it was only hypothesis four which was
confirmed. Hypotheses one, two, three, five and six were not confirmed and the summary
of the results are contained in table 5.39. The interpretations have been made using
statistical knowledge and the existing body of theoretical and empirical literature.
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Table 5.45: Summary of Research Objectives, Hypotheses and Test Results
Research Objectives Hypotheses Hypotheses
Test Results
Objective 1
To examine how CG affects firm
performance among the listed
companies in EAC securities exchanges.
Hypothesis 1
There is no significant relationship
between CG and firm performance
among the listed companies at the EAC
security exchanges.
NOT
CONFIRMED
Objective 2
To assess the relationship between CG
and capital structure.
Hypothesis 2
There is no significant relationship
between CG and capital structure.
NOT
CONFIRMED
Objective 3
To determine the relationship between
capital structure and firm performance.
Hypothesis 3
There is no significant relationship
between capital structure and firm
performance.
NOT
CONFRIMED
Objective 4
To establish the moderating effect of
regulatory compliance on the
relationship between CG and firm
performance.
Hypothesis 4
There is no significant effect of rules
and regulations on the relationship
between CG and firm performance
NOT
CONFIRMED
Objective 5
To determine the intervening effect of
capital structure on the relationship
between corporate governance and firm
performance.
Hypothesis 5
There is no significant intervening effect
of capital structure on the relationship
between corporate governance and firm
performance
NOT
CONFIRMED
Objective 6
To establish the joint effect of capital
structure and regulatory compliance on
the relationship between corporate
governance and firm performance
Hypothesis 6
There is no significant joint effect of
capital structure and regulatory
compliance on the relationship between
CG and firm performance
NOT
CONFIRMED
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CHAPTER SIX
SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
6.1 Introduction
This chapter presents the summary of study, conclusions, recommendations and policy
implications, limitations of the study and suggestions for future research.
6.2 Summary
The main objective of this research study was to examine the effect of capital structure
and regulatory compliance on the relationship between CG and firm performance among
the listed companies at the EACSE. To address this objective, a checklist based on the
CG principles and Corporate Laws was compiled and a comprehensive analysis of the
financial statements done.
In chapter one the study looked at the background of the study where the main variables
in the study were discussed. The study variables included CG as the independent
variable while firm performance was the dependent variable; capital structure and
regulatory compliance were intervening and moderating variables respectively. The main
objective of the study was also indicted plus the six specific objectives were discussed.
The contribution of the study to theory and practice was also elaborated the research
problem statement was discussed including the research questions. The contribution of
the study to theory and practice was also elaborated.
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The theoretical background and empirical literature review was discussed in chapter two.
Among the theories discussed included the agency theory, steward theory, stakeholders
theory and institutional theory. The agency relationship was defined as one that emanates
from the owner’s inability to run the company on a day-to-day basis. In the discussion of
agency theory, two agency relationships emerged, namely the manager- shareholder
relationship and the shareholder-debtholder relationship. The Chapter indicated how
agency conflicts arise, say, when the principal and the agent have different interests.
Jensen and Meckling (1976) described the costs of monitoring the agent as exorbitant.
The agency theory thus provided a theoretical framework of CG by explaining the
problems caused by the separation of ownership to control, which is the basic corporate
governance problem.
The study went on to explore the development of CG in Kenya, Tanzania, Uganda and
Rwanda. The discussion of historical developments established that the evolution of CG
in East Africa has been promoted by efforts to improve CG. The evolution of CG was
based on events such as the collapse of Enron and WorldCom and the privatization of the
government owned enterprises. Recent CG practices in these countries were spearheaded
by the need to promote higher standards of ethical conduct in companies and a range of
legislation and codes of good corporate governance that promote accountability and
transparency in the use of shareholders’ capital.
The discussions in chapter three provided the theoretical basis of the research instrument
used in this study. The CG was measured by constructing the CGI which was based on
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the CG codes and best practices. The CGI was into five sub indices (board structure and
composition, ownership and shareholding, transparency, disclosures and auditing, board
remuneration and corporate ethics). A checklist to be used to assess the annual reports of
the listed companies at the EACSE was formulated. The regulatory compliance was
measured by the RCI which considered the adoption of the shareholders rights, minority
shareholders rights, creditor’s rights and accounting standards disclosure. The checklist
was based on the Companies Act, the listing rules and the CG codes. The capital structure
was measured by considering the debt equity ratio, while firm performance was measured
by ROA, Tobin Q and COC. In order to determine the amount and the quality of
information disclosed in each of the above specific areas and decide whether a company
has fully disclosed, not disclosed or partly disclosed the required corporate governance
information in its annual report reliability and validity of the instruments was tested
Data analysis, presentation and interpretation were emphasized in chapter four. In chapter
five the hypotheses were tested and discussions on the findings of the study analysed.
Data was analysis using SPSS version 20. Descriptive statistics such mean and standard
deviation was analyzed and discussed. The hypotheses of the study were tested using
simple and multiple regressions. Corrections were also conducted between various study
variables. Summary, conclusion and recommendations are also discussed.
6.3 Conclusions
The study has indicated that good CG enhances firm performance and this has supported
the existing literature. The inclusion of capital structure as an intervening variable has
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influenced the interactions between CG and firm performance was positively significant,
while the moderating effect of regulatory compliance on the relationship between CG and
firm performance was also significant as measured by ROA. The joint effect of CG,
capital structure and regulatory compliance also influenced firm performance positively.
Therefore the importance of CG cannot be over-emphasized since it enhances the
organizational climate for the internal structures and performance of a company. Indeed,
CG brings to bear through external independent directors, new dimension for effective
running of a corporate entity thereby enhancing a firm’s corporate entrepreneurship and
competitiveness. The adoption of corporate principles is a giant step towards creating
safeguards against corruption and mismanagement, promoting transparency in economic
life and attracting more domestic and foreign investment. In addition an effective
program to combat corruption is also capable of protecting shareholder value is an
important requirement for improvement of CG practices in East Africa.
Corporate governance was measured by corporate governance index, which was divided
into five sub-indices (sub-index A, sub-index B, sub-index C, sub-index D and sub-index
E). The index was constructed for each and every company as well as per country. The
mean CGI for the East African countries was 76.27% which is an indication of good
corporate governance. The means for the companies listed NSE was 73.8%, DSE
81.08%, USE 79.28% and RSE 70.92%. The board structure and composition had the
highest mean of 80% while ownership and shareholding had the lowest mean of 67.36%.
Most of the quoted companies had the right size of board of directors, there was a clear
separation of CEO and Chairman of the board, the roles and the functions of board were
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actually clearly stated, and the companies provided information about independent
directors. The mean on the ownership and shareholding was low in that most of the
companies did not provide information on the staff share ownership and the block share
ownership of the CEO and the chairman.
The finding also shows that firm’s compliance increases to significant level when
regulation exists in the business environment. CG regulations are mostly to comply or
explain in the East African securities exchanges. However the CGI indicates that more of
the companies follow full compliance with CG regulatory compliance. Higher CGI scores
have significant relationship with the regulatory compliance index. This implies that
voluntary regulation has a positive impact on compliance with regulations. Firms also
practice better compliance with the increasing life of the business and the listing tenure of
the firm. All the sectors of the listed companies have a significant relationship with the
CGI. The purpose of the study was to establish the relationship between corporate
governance and financial performance. From the discussion above, we can therefore
conclude that there exists a positive relationship between corporate governance and
financial performance. Prior research also indicates that corporate governance is
positively related to financial performance.
There is also evidence that good CG practices may lead to lower COC and greater market
valuations for companies. Investors in countries with poor legal protection discount the
prices of firms to compensate for expropriation. However, lower stock prices may not
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raise demand enough in these countries, keeping the supply of outside equity limited
(Shleifer and Wolfenzon 2002).
6.4 Contribution to knowledge
The driving force of CG reforms is to meet the regulatory requirements in EACSE listed
companies; however, the study encourages listed companies to take a more
comprehensive approach to perfect their governance system. That is, this study looked at
the combative effect of capital structure and regulatory compliance on the relationship
between CG and firm performance. Therefore, these findings have made several
contributions to the study of CG. Firstly, the study constructs a CGI evaluate the quality
of CG from the perspectives of board structure and composition, ownership and
shareholding, transparency, disclosure and auditing, board remuneration, and corporate
ethics and build a link between CG and firm performance in EAC listed companies.
Secondly, I established a new conceptual model to enrich the understanding of CG
through integrating capital structure and regulatory compliance into to the relationship
between CG and firm performance. Thirdly, the study validated the moderating and the
intervening effect of the impact of capital structure and regulatory compliance on linkage
between CG and firm performance. The research provides an integration approach to
improve the effectiveness of CG and suggests a more comprehensive understanding of
the system of CG because prior studies often ignored some important moderating and
intervening variables that can have significant impacts on the CG system. The study also
tested the moderating effect of regulatory compliance on CG and firm performance
191
relationship and the findings revealed that regulatory compliance has a moderating effect
on relationship. This study has contributed to existing knowledge by empirically
confirming that regulatory compliance has a moderating variable between CG and firm
performance.
The study also tested the intervening effect of capital structure on corporate governance
and firm performance, which was confirmed. In this study, a comparative analysis of the
of companies listed at NSE, DSE, USE and RSE based on the study variables has also
been done, which no other study known to the researcher has attempted to do. Most of the
previous related studies have been done in the developed countries; hence the findings of
these studies may not be applicable to organizations in developing countries due to
contextual differences. The findings of this study would therefore be more relevant in the
East African context.
In summary, a large number of studies have investigated the impact of CG on firm
performance or market valuation in the developed markets and in the emerging
economies. However, findings showed that effect of CG on the firm performance are
mixed based on a single mechanism of CG. Therefore, this study combined some
important mechanisms into a CGI and examines the effect of CG on firm performance
from a comprehensive perspective.
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6.5 Limitations of the study
First, the study was based on the listed companies at the East African securities exchange
which may limit the generalisation of results to other jurisdictions such as to developed
countries or to the non listed companies. The population from which the sample is drawn
was all the listed companies therefore, results of this study may not be generalised to
smaller and non-listed companies.
Secondly, study only integrated only five important variables of CG: board structure and
composition, ownership and shareholding, transparency, disclosures and auditing, board
remuneration and corporate ethics. However, there is a variety of other important
governance variables that have important effects on financial performance and are not
included in this framework, such as state owned shares. In addition, this study only
investigated some the board of directors‘ characteristics including board size, share
ownership, frequency of board meeting and board remuneration; however, other
characteristics (such as age, education, gender and so on) might also strongly influence
the relationship between CG and firm performance.
Thirdly, the study has assessed the interactive relationship between the CG and capital
structure; however, I also acknowledge the possibility that capital structure decisions
characteristics can influence the individual governance variables.
Finally, the capital markets developments in the EAC are at different levels. Kenya has
got sixty one (61) listed companies while Tanzania and Uganda have got sixteen (16)
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each while Rwanda have got only five (5) listed companies. Burundi still does not have a
security exchange; most of their funds are generated through loans from commercial
banks. The cross-sectional analysis was not very effective in that some of the companies
had not implemented the CG guidelines fully due to the stage of capital markets
developments.
Despite the above limitations, the quality of the study was not compromised. The study
has made an immense contribution to the existing body of knowledge, especially in the
area of CG which has not been fully exploited.
6.6 Recommendations and Policy Implications
The research results showed that there is a positive significant relationship between CG
and firm performance. The relationship is enhanced when the moderating, intervening
and the joint effect of capital structure and regulatory compliance are taken into
consideration. Therefore, the study contributes to policy implications in that the adopting
good CG is an effective way for improving firm performance. Companies should strive at
increasing their CG rating so that the firm value can also be increased. Improving CG
will involve having the optimal board of directors, having independent board of directors
who are outsiders, making full discloser of shareholdings and lasting disclosing the
remuneration of the CEOs.
The mixed results of the governance indicators in EACSE emphasized that good CG
should meet the needs of its institutional conditions and environment. That is, an
arrangement of CG must be situated in a specific historical, social and organizational
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context because institutional differences give rise to governance arrangements that are
suitable for the individual firm and the context in which it is situated. The results show
that board structure, and board composition, and block shareholders’ holdings were
significantly positive with the firm performance. However, the results do not support the
impact of the board size are not consistent with prior results of some developed countries,
these findings demonstrate that the current reform of CG should not adopt the ―one-
size-fits-all.
The third contribution of this study findings is that it is necessary for the government
authorities and regulators is to issue a series of regulations and policies to strength the
importance of CG. For instance, Code of Corporate Governance emphasis that the BOD
should possess adequate professional background (including: knowledge, skills and
qualities) to perform their duties; in addition, the Code also emphasis that NED bear the
responsibilities of due diligence and perform their duties in accordance with laws and
regulations.
The fifth contribution is that the integrated model not only enrich the existing academic
framework of CG through combining capital structure and regulatory compliance into
CG, but also offer a new way to further integrate of other important intervening factors
into CG. That is, the research provides an initial integration approach to improve the
effectiveness of CG and suggests a more comprehensive understanding of the system of
CG because previous studies often ignored some important intervening variables that can
have significant moderating impacts on the effectiveness of CG.
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In conclusion, there is also the need to improve the quality of corporate reporting in the
annual report. The information should be of high quality, because high quality
information will have a positive influence on the investment decisions of capital
providers and other stakeholders. There is also need to improve compliance in so far as
the listed companies are concerned and this requires a change in corporate culture on the
part of the listed companies themselves. It is equally important that directors discharge
their duties under the common law effectively and oversee compliance with legislation. It
is therefore recommended that the CMA must continue to sensitise listed companies and
encourage them to comply with all the provisions of the corporate governance codes.
6.7 Suggestions for Future Research
This study considered only the companies that are listed at the East African securities
exchange. Future researchers could consider carrying out a similar study in a different
sector or sectors to assess any variation in responses. Future researchers could also
introduce different variables other than capital structure and regulatory compliances, and
testing for moderation or intervening effect of such variables on the relationship between
corporate governance and firm performance. Also future research needs to look at non-
financial performance measures.
Replication of this research using data from other international stock markets is likely to
provide insight into different markets responses to CG, capital structure, regulatory
compliance and firm performance. Furthermore, as motives for practising good CG is
196
well covered in the literature, it would also be of great interest if future research could
address the issue of manager’s motives for complying with CG, whether that is to
increase perceived reporting quality, to satisfy shareholders and regulators, or to achieve
some other objectives. A similar study can also be conducted in other settings with
similar market environments for example in other African countries as well as developed
countries.
197
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APPENDICES
APPENDIX I: DATA CAPTURE FORM: REGULATORY COMPLIANC E
INDEX
NAME OF THE COMPANY………..……………………..SERIAL NO/002/2014
REGULATORY COMPLIANCE INDEX Award “1”
if firm
comply and
“0” if not
009 010 011 012 013 TOTAL
A. The Shareholders
1. Origin(identifies the legal origin of the
company law or governance code, equals to
one if common law otherwise zero)
2. Proxy voting by mail is allowed
3. Employees represented in the board
4. Nomination to the board by shareholders
5. Tenure on the board is more than 4 years
6. Cross-shareholdings between 2
independent companies
7. There is a requirement to Deposit/Register
shares prior to a general meeting
8. Shareholders’ approval of anti-takeover
defense measures is required.
9. Shareholders’ approval of preemption
rights is required
10. The CEO cannot be the chairman of the
board of directors (in 1-tier board structure)
11. Requirement to disclose any transactions
between management and company
12. Disclosure of managerial compensation
212
requirement
B. The minority shareholders
13. Minority representation on the board
otherwise.
14. Voting caps limiting power of large
shareholders
15. One-share-one-vote rule
16. Mandatory disclosure of large ownership
stakes
17. Shares not blocked before voting
18. Cumulative voting or proportional
representation
19. Mandatory dividend which equals the
percentage of net income that the company
law requires
C. The creditors
20. There is a reorganization option to protect
creditors
21. Automatic stay on the assets is obliged in
reorganization
22. Secured creditors are ranked first
23. Creditor approval is required under
bankruptcy
24. Appointment of official to manage
reorganization/liquidation procedure
25. The country imposes restrictions on the
creditors consent for reorganization
26. Secured creditors are able to gain
possession of their security once the
213
reorganization petition has been approved
27. The debtor does not retain the
administration of its property pending the
resolution of the reorganization
28. There is a the minimum percentage of total
share capital mandated by corporate law to
avoid the dissolution of an existing firm
D. Accounting Standards Disclosure
29. General Information (Name of the
company, purpose, legal status, brief
history and overview of the main
subsidiaries).
30. Income statements are disclosed
31. Balance Sheet
32. Funds Flow Statement
33. Accounting Standards applied
34. Stock Data indicated
35. Special items are indicated on the footnotes
214
APPENDIX II: DATA CAPTURE FORM: CORPORATE GOVERNANC E INDEX
(CGI)
NAME OF THE COMPANY……………………………… SERIAL NO/001/2014
CORPORATE GOVERNANCE
INDEX (CGI)
“1” if is yes
and “0” if
the response
is no
009 010 011 012 013 TOTAL
Sub Index A: Board Structure
and Composition
1. Board size is between 6-9
2. Role and functions of board
is stated
3. Chairman and CEO
separation
4. Information about
independent directors
5. Board meeting attendance
6. Outside directors attendance
in meetings
7. Existence of the position of
CFO
8. Directors representing
minority shareholders
9. Biography of the board
members
10. Changes is the board
structure is indicated
Sub Index B: Ownership and
215
Share holding
1. Presence of outside
blockholders (more than
10%)
2. The CEO own shares
3. Directors ownership (block
ownership) other than the
CEO and Chairman
4. Chairman or CEO is block
holder (10%)
5. Concentration of ownership
(top five)
6. Dividend policy
7. Disclosure of staff benefits
other than wages and salaries
8. Disclosure of company
secretary in annual report
with description of duties and
roles
Sub Index C: Transparency,
Disclosures and Auditing
1. The company have full
disclosure of CG practices
2. Disclosure of payment to
auditors for consulting and
other work
3. Internal audit committee
4. Board of directors and
executive staff members
216
remuneration
5. Annual report of share
ownership
6. Employee ownership
7. Auditor appointment and
rotation
8. Annual reports through
internet
9. Disclosure of other events in
the internet
10. Chairman’s statement
Sub Index D: Board
Remuneration
1. Remuneration committee
2. Composition of the
remuneration committee
3. Policy framework for the
remunerating committee
4. Remuneration committee
comprises non-executive
board members
5. CEO compensation is
disclosed
6. Compensation in form of
stock bonus
7. Loans or advances to board
members not provided
217
8. Balance between guaranteed
salary and performance
element (share option)
9. Remuneration policy
disclosed in annual report
10. Majority of the remuneration
committee members are non-
executive
Sub Index E: Corporate Ethics
1. Corporate ethics committee
in place
2. Code of ethical conduct
3. Code of conduct is published
4. Notice of annual general
meeting
5. Agenda of the annual general
meeting
6. Compliance with CMA
guidelines
7. Environmental and social
responsibility
8. Disclosure of adherence to
the company’s code of ethics
Source: Black et al. (2006)
218
APPENDIX III: FIRMS LISTED AT EAC SECURITIES EXCHAN GES
Kenya
Nairobi Securities Exchange (NSE)
1 Eaagads Ltd
2 Kapchorua Tea Co. Ltd
3 Kakuzi
4 Limuru Tea
5 Rea Vipingo Plantations Ltd
6 Sasini Ltd
7 Williamson Tea Kenya Ltd
8 Express Ltd
9 Kenya Airways Ltd
10 Nation Media Group
11 Standard Group Ltd
12 TPS Eastern Africa (Serena) Ltd
13 Scangroup Ltd
14 Uchumi Supermarket Ltd
15 Hutchings Biemer Ltd
16 Longhorn Kenya Ltd
17 Access Kenya Group Ltd
18 Safaricom Ltd
19 Car and General (K) Ltd
20 CMC Holdings Ltd
21 Sameer Africa Ltd
22 Barclays Bank Ltd
23 CFC Stanbic Holdings Ltd
24 I & M Holdings Ltd
25 Diamond Trust Bank Kenya Ltd
26 Housing Finance Co. Ltd
27 Kenya Commercial Bank Ltd
219
28 National Bank of Kenya Ltd
29 NIC Bank Ltd
30 Standard Chartered Bank Ltd
31 Equity Bank Ltd
32 The Co-operative Bank Ltd
33 Jubilee Holding Ltd
34 Pan Africa Insurance Holdings Ltd
35 Kenya Re-Insurance Corporation Ltd
36 Liberty Kenya Holdings Ltd
37 British-American Investment Company (Kenya) Ltd
38 CIC Insurance Group Ltd
39 Olympia Capital Holdings Ltd
40 Centum Investment Co. Ltd
41 Trans-Century
42 B.O.C Kenya Ltd
43 British American Tobacco Kenya Ltd
44 Carbacid Investments Ltd
45 East African Breweries Ltd
46 Mumias Sugar Co. Ltd
47 Unga Group Co. Ltd
48 Eveready East Africa Ltd
49 Kenya Orchards Ltd
50 A. Baumann Co. Ltd
51 AthiRiver Mining
52 Bamburi Cement Ltd
53 Crown Berger Ltd
54 E.A Cables Ltd
55 E.A. Portland Cement Ltd
56 KenolKobil Ltd
57 Total Kenya Ltd
220
58 KenGen Ltd
59 Kenya Power & Lighting Co. Ltd
60 Umeme ltd
61 Home Afrika Ltd
Uganda
Uganda Securities Exchange (USE)
1 British American Tobacco Uganda
2 Bank of Baroda
3 Development Finance Company of Uganda Ltd
4 East African Breweries Ltd *
5 Jubilee Holdings Ltd *
6 Kenya Airways *
7 New Vision Printing and Publishing Company Ltd
8 Stanbic Bank Uganda
9 Uganda Clays Ltd
10 Equity bank Ltd *
11 KCB Group *
12 National Insurance Corporation
13 Nation Media Group*
14 Centum Investment Company ltd*
15 Umeme Ltd *
16 Uchumi Ltd *
Tanzania
Dar es Salaam Stock Exchange (DSE)
1 TOL Gases Ltd
2 Tanzania Breweries Ltd
3 TATEPA Ltd
4 Tanga Cement Co. Ltd
5 Swissport Tanzania Ltd
6 Tanzania Portland Cement Co. Ltd
221
7 DCB Commercial Bank Plc
8 National Microfianance Bank
9 CRDB Bank Plc
10 Precision Air Services Plc
11 Kenya Airways Ltd*
12 East African Breweries Ltd*
13 Jubilee Holdings Ltd *
14 Kenya Commercial Bank Ltd*
15 Nation Media Group Plc *
16 African Barrick Gold Plc
Rwanda
Rwanda Stock Exchange
1 Bank of Kigali
2 Bralirwa Ltd
3 Kenya Commercial Bank Ltd*
4 Nation Media Group ltd *
5 Uchumi Supermarket Ltd*
* Cross listed firms
Source: http://www.nse.co.ke,www.use.or.og,www.des.co.tz and www.rse.rw
222
APPENDIX IV: DATA ASSUMPTIONS
Tolerance
Coefficientsa
Model Unstandardized
Coefficients
Standardized
Coefficients
t
B Std. Error Beta
1
(Constant) 2009.839 1.060 1896.693
Lnassets .085 .047 .114 1.799
LEVERAGE RATIO .238 .370 .041 .644
ROA -.434 .863 -.051 -.503
COC = COST OF
CAPITAL -2.520 2.164 -.076 -1.165
TOBIN Q .058 .140 .032 .419
RCI -1.121 2.162 -.077 -.519
CGI .612 2.089 .045 .293
Coefficientsa
Model Sig. Collinearity Statistics
Tolerance VIF
1
(Constant) .000
Lnassets .073 .900 1.111
LEVERAGE RATIO .520 .892 1.121
ROA .616 .343 2.911
COC = COST OF CAPITAL .245 .839 1.192
TOBIN Q .676 .626 1.597
RCI .604 .164 6.099
CGI .770 .150 6.678
223
a. Dependent Variable: Year
Collinearity Diagnosticsa
Model Dimension Eigenvalue Condition
Index
Variance Proportions
(Constant) Lnassets LEVERAGE
RATIO
1
1 6.649 1.000 .00 .00 .01
2 .586 3.369 .00 .00 .11
3 .453 3.830 .00 .00 .45
4 .179 6.099 .00 .01 .19
5 .116 7.560 .00 .00 .22
6 .010 25.442 .00 .60 .01
7 .005 35.718 .80 .38 .01
8 .002 57.153 .19 .00 .01
Collinearity Diagnosticsa
Model Dimension Variance Proportions
ROA COC = COST OF
CAPITAL
TOBIN Q RCI CGI
1
1 .00 .00 .00 .00 .00
2 .08 .20 .04 .00 .00
3 .00 .32 .01 .00 .00
4 .38 .27 .05 .00 .00
5 .05 .05 .89 .00 .00
6 .32 .03 .00 .14 .04
7 .10 .12 .01 .15 .00
8 .07 .00 .00 .70 .96
224
a. Dependent Variable: Year
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value 2010.32 2011.59 2011.00 .221 280
Residual -2.305 2.490 .000 1.399 280
Std. Predicted
Value -3.081 2.647 .000 1.000 280
Std. Residual -1.627 1.757 .000 .987 280
a. Dependent Variable: Year
T-Test
Group Statistics
VAR00001 N Mean Std. Deviation Std. Error
Mean
LEVERAGE RATIO 1.00 140 .293289 .2073572 .0175249
2.00 140 .295440 .2741245 .0231677
ROA 1.00 140 .208822 .1616902 .0136653
2.00 140 .201441 .1740580 .0147106
TOBIN Q 1.00 140 1.335727 .7517707 .0635362
2.00 140 1.333339 .7875841 .0665630
COC = COST OF
CAPITAL
1.00 140 .052058 .0446238 .0037714
2.00 140 .049770 .0410415 .0034686
CGI 1.00 140 .729267 .1027655 .0086853
2.00 140 .724413 .1073876 .0090759
RCI 1.00 140 .559929 .0961152 .0081232
2.00 140 .553357 .0979327 .0082768
Lnassets 1.00 140 16.334993 1.8314363 .1547846
2.00 140 16.731576 1.9277916 .1629281
225
Independent Samples Test
Levene's Test for Equality of
Variances
t-test for
Equality
of Means
F Sig. t
LEVERAGE RATIO
Equal variances assumed 4.294 .039 -.074
Equal variances not
assumed
-.074
ROA
Equal variances assumed .690 .407 .368
Equal variances not
assumed
.368
TOBIN Q
Equal variances assumed 1.257 .263 .026
Equal variances not
assumed
.026
COC = COST OF
CAPITAL
Equal variances assumed .481 .488 .447
Equal variances not
assumed
.447
CGI
Equal variances assumed .644 .423 .386
Equal variances not
assumed
.386
RCI
Equal variances assumed .240 .624 .567
Equal variances not
assumed
.567
Lnassets
Equal variances assumed .306 .581 -1.765
Equal variances not
assumed
-1.765
226
Independent Samples Test
t-test for Equality of Means
df Sig. (2-tailed) Mean
Difference
LEVERAGE RATIO
Equal variances assumed 278 .941 -.0021513
Equal variances not
assumed 258.835 .941 -.0021513
ROA
Equal variances assumed 278 .713 .0073811
Equal variances not
assumed 276.503 .713 .0073811
TOBIN Q
Equal variances assumed 278 .979 .0023880
Equal variances not
assumed 277.400 .979 .0023880
COC = COST OF
CAPITAL
Equal variances assumed 278 .656 .0022879
Equal variances not
assumed 276.076 .656 .0022879
CGI
Equal variances assumed 278 .699 .0048540
Equal variances not
assumed 277.464 .699 .0048540
RCI
Equal variances assumed 278 .571 .0065714
Equal variances not
assumed 277.902 .571 .0065714
Lnassets
Equal variances assumed 278 .079 -.3965831
Equal variances not
assumed 277.272 .079 -.3965831
Independent Samples Test
t-test for Equality of Means
227
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower
LEVERAGE RATIO Equal variances assumed .0290494 -.0593360
Equal variances not assumed .0290494 -.0593545
ROA Equal variances assumed .0200784 -.0321439
Equal variances not assumed .0200784 -.0321449
TOBIN Q Equal variances assumed .0920189 -.1787544
Equal variances not assumed .0920189 -.1787561
COC = COST OF
CAPITAL
Equal variances assumed .0051240 -.0077987
Equal variances not assumed .0051240 -.0077991
CGI Equal variances assumed .0125621 -.0198749
Equal variances not assumed .0125621 -.0198751
RCI Equal variances assumed .0115971 -.0162578
Equal variances not assumed .0115971 -.0162579
Lnassets Equal variances assumed .2247306 -.8389729
Equal variances not assumed .2247306 -.8389780
Independent Samples Test
t-test for Equality of
Means
95% Confidence
Interval of the
Difference
Upper
LEVERAGE RATIO Equal variances assumed .0550334
Equal variances not assumed .0550519
ROA Equal variances assumed .0469061
Equal variances not assumed .0469070
228
TOBIN Q Equal variances assumed .1835304
Equal variances not assumed .1835321
COC = COST OF CAPITAL Equal variances assumed .0123746
Equal variances not assumed .0123749
CGI Equal variances assumed .0295829
Equal variances not assumed .0295831
RCI Equal variances assumed .0294007
Equal variances not assumed .0294007
Lnassets Equal variances assumed .0458068
Equal variances not assumed .0458119
Oneway
ANOVA
Sum of
Squares
df Mean
Square
F
LEVERAGE RATIO
Between Groups .000 1 .000 .005
Within Groups 16.422 278 .059
Total 16.422 279
ROA
Between Groups .004 1 .004 .135
Within Groups 7.845 278 .028
Total 7.849 279
TOBIN Q
Between Groups .000 1 .000 .001
Within Groups 164.777 278 .593
Total 164.778 279
COC = COST OF
CAPITAL
Between Groups .000 1 .000 .199
Within Groups .511 278 .002
Total .511 279
CGI Between Groups .002 1 .002 .149
Within Groups 3.071 278 .011
229
Total 3.073 279
RCI
Between Groups .003 1 .003 .321
Within Groups 2.617 278 .009
Total 2.620 279
Lnassets
Between Groups 11.009 1 11.009 3.114
Within Groups 982.805 278 3.535
Total 993.814 279
ANOVA
Sig.
LEVERAGE RATIO
Between Groups .941
Within Groups
Total
ROA
Between Groups .713
Within Groups
Total
TOBIN Q
Between Groups .979
Within Groups
Total
COC = COST OF CAPITAL
Between Groups .656
Within Groups
Total
CGI
Between Groups .699
Within Groups
Total
RCI
Between Groups .571
Within Groups
Total
Lnassets Between Groups .079
Within Groups
230
Total
Regression
Variables Entered/Removeda
Model Variables Entered Variables Removed Method
1 LEVERAGE RATIOb Enter
a. Dependent Variable: ROA
b. All requested variables entered.
Model Summaryb
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
Durbin-
Watson
1 .129a .017 .013 .1666219 1.407
a. Predictors: (Constant), LEVERAGE RATIO
b. Dependent Variable: ROA
ANOVA a
Model Sum of
Squares
df Mean Square F Sig.
1
Regression .131 1 .131 4.714 .031b
Residual 7.718 278 .028
Total 7.849 279
a. Dependent Variable: ROA
b. Predictors: (Constant), LEVERAGE RATIO
Coefficientsa
231
Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) .231 .016 14.765 .000
LEVERAGE
RATIO -.089 .041 -.129 -2.171 .031
a. Dependent Variable: ROA
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value .081027 .231322 .205132 .0216591 280
Residual -.6667493 .3921452 0E-7 .1663231 280
Std. Predicted
Value -5.730 1.209 .000 1.000 280
Std. Residual -4.002 2.354 .000 .998 280
a. Dependent Variable: ROA
Regression
Variables Entered/Removeda
Model Variables
Entered
Variables
Removed
Method
1 TOBIN Qb . Enter
a. Dependent Variable: ROA
b. All requested variables entered.
Model Summaryb
232
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
Durbin-
Watson
1 .545a .297 .295 .1408493 1.525
a. Predictors: (Constant), TOBIN Q
b. Dependent Variable: ROA
ANOVA a
Model Sum of
Squares
df Mean Square F Sig.
1
Regression 2.334 1 2.334 117.642 .000b
Residual 5.515 278 .020
Total 7.849 279
a. Dependent Variable: ROA
b. Predictors: (Constant), TOBIN Q
Coefficientsa
Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) .046 .017 2.742 .007
TOBIN Q .119 .011 .545 10.846 .000
a. Dependent Variable: ROA
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value .061243 .614264 .205132 .0914607 280
Residual -.5804526 .3860784 0E-7 .1405967 280
Std. Predicted
Value -1.573 4.473 .000 1.000 280
233
Std. Residual -4.121 2.741 .000 .998 280
a. Dependent Variable: ROA
Regression
Variables Entered/Removeda
Model Variables
Entered
Variables
Removed
Method
1
COC = COST
OF
CAPITALb
. Enter
a. Dependent Variable: ROA
b. All requested variables entered.
Model Summaryb
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
Durbin-
Watson
1 .228a .052 .048 .1636104 1.531
a. Predictors: (Constant), COC = COST OF CAPITAL
b. Dependent Variable: ROA
ANOVA a
Model Sum of
Squares
df Mean Square F Sig.
1
Regression .407 1 .407 15.218 .000b
Residual 7.442 278 .027
Total 7.849 279
a. Dependent Variable: ROA
b. Predictors: (Constant), COC = COST OF CAPITAL
Coefficientsa
234
Model Unstandardized
Coefficients
Standardized
Coefficients
t
B Std. Error Beta
1
(Constant) .251 .015 16.475
COC = COST OF
CAPITAL -.893 .229 -.228 -3.901
Coefficientsa
Model Sig.
1 (Constant) .000
COC = COST OF CAPITAL .000
a. Dependent Variable: ROA
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value -.036661 .248792 .205132 .0382108 280
Residual -.5754753 .4177210 0E-7 .1633169 280
Std. Predicted
Value -6.328 1.143 .000 1.000 280
Std. Residual -3.517 2.553 .000 .998 280
a. Dependent Variable: ROA
Regression
Variables Entered/Removeda
Model Variables
Entered
Variables
Removed
Method
1 RCIb . Enter
235
a. Dependent Variable: ROA
b. All requested variables entered.
Model Summaryb
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
Durbin-
Watson
1 .746a .556 .554 .1119864 1.535
a. Predictors: (Constant), RCI
b. Dependent Variable: ROA
ANOVA a
Model Sum of
Squares
df Mean Square F Sig.
1
Regression 4.363 1 4.363 347.867 .000b
Residual 3.486 278 .013
Total 7.849 279
a. Dependent Variable: ROA
b. Predictors: (Constant), RCI
Coefficientsa
Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) -.513 .039 -13.128 .000
RCI 1.290 .069 .746 18.651 .000
a. Dependent Variable: ROA
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value .003011 .390110 .205132 .1250459 280
Residual -.4692174 .2539694 0E-7 .1117855 280
Std. Predicted
Value -1.616 1.479 .000 1.000 280
236
Std. Residual -4.190 2.268 .000 .998 280
a. Dependent Variable: ROA
Regression
Variables Entered/Removeda
Model Variables
Entered
Variables
Removed
Method
1 Lnassetsb . Enter
a. Dependent Variable: ROA
b. All requested variables entered.
Model Summaryb
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
Durbin-
Watson
1 .070a .005 .001 .1676158 1.440
a. Predictors: (Constant), Lnassets
b. Dependent Variable: ROA
ANOVA a
Model Sum of
Squares
df Mean Square F Sig.
1
Regression .039 1 .039 1.372 .243b
Residual 7.810 278 .028
Total 7.849 279
a. Dependent Variable: ROA
b. Predictors: (Constant), Lnassets
Coefficientsa
Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) .102 .088 1.155 .249
237
Lnassets .006 .005 .070 1.171 .243
a. Dependent Variable: ROA
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value .174502 .251626 .205132 .0117522 280
Residual -.6244779 .3915339 0E-7 .1673152 280
Std. Predicted
Value -2.606 3.956 .000 1.000 280
Std. Residual -3.726 2.336 .000 .998 280
a. Dependent Variable: ROA
238
APPENDIX V: DATA SUMMARY 2009-2013 AT EACSE
Country Year CG RCI CS ROA TOBIN Q COC
Kenya 2009 0.61000 0.45000 0.39230 0.20000 0.55940 0.15670
Kenya 2009 0.63043 0.47000 0.33810 0.19000 0.48110 0.12000
Kenya 2009 0.84783 0.70000 0.27470 0.14230 1.46030 0.06000
Kenya 2009 0.87000 0.65000 0.11000 0.27400 0.84690 0.03980
Kenya 2009 0.65217 0.47000 0.24020 0.12330 0.50000 0.08990
Kenya 2009 0.54000 0.42000 0.16300 -0.16390 0.60000 0.15000
Kenya 2009 0.73913 0.56000 0.19700 0.17460 1.70360 0.08700
Kenya 2009 0.69565 0.55000 0.17972 0.10920 0.60000 0.08000
Kenya 2009 0.60000 0.44000 0.25842 0.01730 0.93710 0.09000
Kenya 2009 0.78000 0.55000 0.28035 0.15200 0.91000 0.03370
Kenya 2009 0.73913 0.60000 0.34761 0.10470 1.29980 0.01780
Kenya 2009 0.69565 0.60000 0.41734 0.23850 1.00370 0.03160
Kenya 2009 0.80435 0.68000 0.29545 0.16470 1.11750 0.01830
239
Kenya 2009 0.70000 0.56000 0.18985 0.08400 0.99790 0.05000
Kenya 2009 0.80435 0.65000 0.11580 0.26150 1.05210 0.03200
Kenya 2009 0.82609 0.70000 0.30222 0.19790 1.24070 0.01990
Kenya 2009 0.69565 0.60000 0.05980 0.21170 1.13570 0.10000
Kenya 2009 0.63043 0.46000 0.40000 0.09000 0.89390 0.10000
Kenya 2009 0.89130 0.70000 0.09000 0.49220 2.85340 0.03870
Kenya 2009 0.80435 0.70000 0.19600 0.27670 1.82920 0.05000
Kenya 2009 0.69565 0.46000 0.46390 0.25070 1.60340 0.03110
Kenya 2009 0.80000 0.68000 0.33210 0.34870 2.20000 0.02960
Kenya 2009 0.62000 0.46000 1.04300 0.06900 0.90000 0.10000
Kenya 2009 0.76087 0.60000 0.32980 0.22820 1.56550 0.00870
Kenya 2009 0.84783 0.70000 0.14400 0.59770 1.67010 0.04660
Kenya 2009 0.78261 0.55000 0.83331 0.15050 0.86880 0.06000
Kenya 2009 0.84783 0.60000 0.33670 0.29710 1.73660 0.02570
Kenya 2009 0.78000 0.55000 0.44610 0.20720 1.09120 0.06100
Kenya 2009 0.60870 0.48000 0.47520 0.08390 0.71150 0.02530
240
Kenya 2009 0.65000 0.45000 0.04723 0.13140 0.91640 0.13000
Kenya 2009 0.60870 0.41000 0.00950 0.00520 1.04200 0.10000
Kenya 2009 0.67391 0.42000 0.04439 0.04650 0.87900 0.12000
Kenya 2009 0.60870 0.44000 0.25965 0.09400 0.50000 0.11000
Kenya 2009 0.84783 0.68000 0.36610 0.49520 0.86130 0.02630
Kenya 2009 0.69565 0.62000 0.35892 0.34520 1.10870 0.00780
Kenya 2009 0.85000 0.68000 0.04679 0.54870 1.96524 0.00506
Kenya 2009 0.73913 0.55000 0.10190 0.20000 1.70150 0.05130
Kenya 2009 0.89130 0.70000 0.26170 0.42100 2.52440 0.03690
Kenya 2009 0.80435 0.65000 0.04470 0.33230 2.50000 0.05000
Kenya 2009 0.84783 0.68000 0.08530 0.60180 2.21020 0.04930
Kenya 2009 0.60870 0.48000 0.38690 0.13660 0.95080 0.04630
Kenya 2009 0.69565 0.48000 0.61970 0.26650 0.70000 0.00650
Kenya 2009 0.89130 0.70000 0.23670 0.33380 2.74980 0.02670
Uganda 2009 0.63043 0.50000 0.19451 0.01830 0.47800 0.09000
Uganda 2009 0.65217 0.44000 0.49190 -0.02710 0.41780 0.10000
241
Uganda 2009 0.60870 0.50000 0.16283 0.07970 0.51020 0.10000
Uganda 2009 0.60870 0.44000 0.08090 0.07910 0.49870 0.08000
Uganda 2009 0.60870 0.46000 0.26982 0.01500 0.52010 0.10000
Uganda 2009 0.59000 0.40000 0.30000 0.07470 0.43000 0.09000
Tanzania 2009 0.69565 0.56000 0.09000 0.22220 1.07036 0.04798
Tanzania 2009 0.63043 0.50000 0.47000 0.05698 0.90000 0.01274
Tanzania 2009 0.90000 0.70000 0.11897 0.52383 2.17374 0.08614
Tanzania 2009 0.89130 0.64000 0.13365 0.49526 2.50559 0.05000
Tanzania 2009 0.89130 0.62000 0.51666 0.40448 2.03502 0.05933
Rwanda 2009 0.73913 0.56000 0.01510 0.34230 1.10000 0.04950
Rwanda 2009 0.54348 0.45000 0.30000 0.06960 0.70000 0.08000
Kenya 2010 0.61000 0.45000 0.26470 0.17000 0.80950 0.10240
Kenya 2010 0.63043 0.47000 0.27380 0.19000 0.63350 0.06230
Kenya 2010 0.84783 0.70000 0.35090 0.25910 2.73260 0.01990
Kenya 2010 0.87000 0.65000 0.08000 0.27010 0.87960 0.02880
Kenya 2010 0.65217 0.47000 0.26630 0.12330 0.44200 0.09220
242
Kenya 2010 0.54000 0.42000 0.44760 -0.16390 0.12550 0.05970
Kenya 2010 0.73913 0.56000 0.15710 0.07460 1.99120 0.01450
Kenya 2010 0.69565 0.55000 0.13649 0.10920 1.35650 0.01890
Kenya 2010 0.60000 0.44000 0.28529 0.01730 0.97070 0.01460
Kenya 2010 0.78000 0.55000 0.23598 0.15200 1.14060 0.02230
Kenya 2010 0.73913 0.60000 0.23846 0.10470 1.50240 0.01590
Kenya 2010 0.69565 0.60000 0.50000 0.23850 1.06280 0.02960
Kenya 2010 0.80435 0.64000 0.28257 0.06470 2.09960 0.01870
Kenya 2010 0.70000 0.56000 0.14153 0.08400 1.01650 0.01670
Kenya 2010 0.80435 0.65000 0.22329 0.16150 2.13830 0.01990
Kenya 2010 0.82609 0.70000 0.25194 0.19790 2.37640 0.01560
Kenya 2010 0.69565 0.60000 0.03967 0.21170 1.30040 0.00920
Kenya 2010 0.63043 0.46000 0.40000 0.07290 1.10610 0.01890
Kenya 2010 0.89130 0.70000 0.08080 0.49220 3.61790 0.03280
Kenya 2010 0.80435 0.70000 0.24390 0.20940 2.37560 0.01000
Kenya 2010 0.69565 0.46000 0.38610 0.27440 0.65160 0.02900
243
Kenya 2010 0.80000 0.60000 0.25220 0.31620 2.23090 0.02460
Kenya 2010 0.62000 0.46000 0.38920 0.06900 0.33960 0.15000
Kenya 2010 0.76087 0.56000 0.50440 0.23760 1.79580 0.01250
Kenya 2010 0.84783 0.70000 0.13050 0.59770 2.38860 0.03160
Kenya 2010 0.78261 0.55000 0.65926 0.15050 0.97560 0.04910
Kenya 2010 0.84783 0.60000 0.44320 0.29710 1.32180 0.03530
Kenya 2010 0.78000 0.55000 0.49110 0.20720 1.12450 0.03210
Kenya 2010 0.60870 0.48000 0.74020 0.08390 0.78120 0.01720
Kenya 2010 0.65000 0.45000 0.04736 0.13140 1.11550 0.09000
Kenya 2010 0.60870 0.41000 0.02050 0.00520 1.02020 0.00410
Kenya 2010 0.67391 0.42000 0.34197 0.04650 0.84980 0.03330
Kenya 2010 0.60870 0.44000 0.21652 0.09400 1.13010 0.00650
Kenya 2010 0.84783 0.68000 0.38760 0.49260 2.77130 0.01970
Kenya 2010 0.69565 0.62000 0.30229 0.34670 1.12290 0.00790
Kenya 2010 0.85000 0.68000 0.02433 0.56182 1.08758 0.00730
Kenya 2010 0.73913 0.55000 0.12160 0.18270 1.52280 0.06470
244
Kenya 2010 0.89130 0.70000 0.18710 0.42100 2.96790 0.03000
Kenya 2010 0.80435 0.65000 0.03310 0.33230 3.64990 0.04760
Kenya 2010 0.84783 0.68000 0.08630 0.60180 4.12210 0.02140
Kenya 2010 0.60870 0.48000 0.23920 0.13660 1.47900 0.03300
Kenya 2010 0.69565 0.48000 0.39600 0.19330 0.51870 0.02990
Kenya 2010 0.89130 0.70000 0.14700 0.33380 2.53150 0.03810
Uganda 2010 0.63043 0.50000 0.16668 0.01830 1.48700 0.32180
Uganda 2010 0.65217 0.44000 0.54700 -0.02710 1.45560 0.05350
Uganda 2010 0.60870 0.50000 0.14410 0.07970 1.49070 0.01766
Uganda 2010 0.60870 0.44000 0.12680 0.07910 0.93860 0.12880
Uganda 2010 0.60870 0.46000 0.47428 0.01500 1.23420 0.12310
Uganda 2010 0.59000 0.40000 0.30000 0.07470 1.14210 0.13730
Tanzania 2010 0.69565 0.56000 0.09000 0.21370 1.00731 0.05234
Tanzania 2010 0.63043 0.50000 0.47000 0.05698 1.04713 0.01274
Tanzania 2010 0.90000 0.70000 0.19642 0.52383 2.08066 0.09623
Tanzania 2010 0.89130 0.64000 0.11284 0.49526 1.44278 0.10629
245
Tanzania 2010 0.89130 0.62000 0.34841 0.40448 1.70998 0.05762
Rwanda 2010 0.73913 0.56000 0.12060 0.34230 3.71060 0.03480
Rwanda 2010 0.54348 0.45000 0.30000 0.06960 1.26080 0.01730
Kenya 2011 0.61000 0.45000 0.25750 0.23000 0.63470 0.14570
Kenya 2011 0.63043 0.47000 0.28960 0.19000 0.59580 0.04940
Kenya 2011 0.84783 0.70000 0.26730 0.22890 0.44450 0.05150
Kenya 2011 0.87000 0.65000 0.00100 0.25790 0.80190 0.03400
Kenya 2011 0.65217 0.47000 0.37210 0.12330 2.06900 0.04620
Kenya 2011 0.54000 0.42000 1.24080 0.13710 0.81440 0.11000
Kenya 2011 0.73913 0.56000 0.25190 0.07460 0.67200 0.05870
Kenya 2011 0.69565 0.55000 0.16875 0.10920 1.30690 0.02030
Kenya 2011 0.60000 0.44000 0.36661 0.01730 0.94420 0.01440
Kenya 2011 0.78000 0.55000 0.33741 0.15200 1.04140 0.02330
Kenya 2011 0.73913 0.60000 0.43144 0.10470 1.13470 0.01980
Kenya 2011 0.69565 0.60000 0.40000 0.26120 0.94150 0.04880
Kenya 2011 0.80435 0.64000 0.22955 0.06470 1.01710 0.02460
246
Kenya 2011 0.70000 0.56000 0.23087 0.08400 0.93030 0.01690
Kenya 2011 0.80435 0.65000 0.18794 0.16150 0.98680 0.02550
Kenya 2011 0.82609 0.70000 0.90000 0.19790 1.15380 0.01800
Kenya 2011 0.69565 0.60000 0.06699 0.21170 1.12970 0.01450
Kenya 2011 0.63043 0.46000 0.50000 0.12700 0.89990 0.02600
Kenya 2011 0.89130 0.70000 0.09340 0.49220 2.80850 0.05190
Kenya 2011 0.80435 0.70000 0.25570 0.30660 1.87910 0.00200
Kenya 2011 0.69565 0.46000 0.56970 0.33440 1.12810 0.02570
Kenya 2011 0.80000 0.60000 0.31580 0.42990 1.01540 0.02420
Kenya 2011 0.62000 0.46000 0.32530 0.06900 1.18650 0.11000
Kenya 2011 0.76087 0.56000 0.66580 0.23290 1.47050 0.01320
Kenya 2011 0.84783 0.70000 0.13410 0.59770 1.63270 0.06620
Kenya 2011 0.78261 0.55000 0.76020 0.15050 0.74450 0.13810
Kenya 2011 0.84783 0.60000 0.60170 0.29710 1.16460 0.03680
Kenya 2011 0.78000 0.55000 0.72870 0.20720 0.95100 0.00990
Kenya 2011 0.60870 0.48000 0.92310 0.08390 0.75380 0.02510
247
Kenya 2011 0.65000 0.45000 0.13129 0.13140 1.06510 0.03000
Kenya 2011 0.60870 0.41000 0.07470 0.00520 0.99980 0.03410
Kenya 2011 0.67391 0.42000 0.32851 0.04650 0.81210 0.05050
Kenya 2011 0.60870 0.44000 0.19458 0.09400 1.06010 0.00690
Kenya 2011 0.84783 0.68000 0.47590 0.41330 0.62580 0.02960
Kenya 2011 0.69565 0.62000 0.20482 0.19600 0.98870 0.01800
Kenya 2011 0.85000 0.68000 0.12152 0.47303 1.28021 0.01000
Kenya 2011 0.73913 0.55000 0.14880 0.20860 1.34340 0.06030
Kenya 2011 0.89130 0.70000 0.23660 0.42100 2.32270 0.05830
Kenya 2011 0.80435 0.65000 0.05960 0.33230 1.94360 0.06190
Kenya 2011 0.84783 0.68000 0.12690 0.60180 3.54170 0.05710
Kenya 2011 0.60870 0.48000 0.34230 0.13660 0.84580 0.05320
Kenya 2011 0.69565 0.48000 0.43620 0.25450 0.47660 0.05120
Kenya 2011 0.89130 0.70000 0.21110 0.33380 1.73910 0.04350
Uganda 2011 0.63043 0.50000 0.20003 0.01830 1.40540 0.05910
Uganda 2011 0.65217 0.44000 0.49190 -0.02710 1.35390 0.05280
248
Uganda 2011 0.60870 0.50000 0.10939 0.07970 1.34390 0.03647
Uganda 2011 0.60870 0.44000 0.08090 0.07910 1.05890 0.04070
Uganda 2011 0.60870 0.46000 0.25192 0.01500 1.22510 0.03210
Uganda 2011 0.59000 0.40000 0.30000 0.07470 1.14110 0.13300
Tanzania 2011 0.69565 0.56000 0.09000 0.20000 1.04450 0.03398
Tanzania 2011 0.63043 0.50000 0.47000 0.05698 1.06499 0.01417
Tanzania 2011 0.90000 0.70000 0.11897 0.52383 1.20874 0.02917
Tanzania 2011 0.89130 0.64000 0.13365 0.49526 1.40899 0.11256
Tanzania 2011 0.89130 0.62000 0.51666 0.40448 1.52726 0.01744
Rwanda 2011 0.73913 0.56000 0.01510 0.34230 3.10480 0.02360
Rwanda 2011 0.54348 0.45000 0.30000 0.06960 1.07580 0.03800
Kenya 2012 0.61000 0.45000 0.18290 0.13000 0.61080 0.21000
Kenya 2012 0.63043 0.47000 0.28400 0.19000 0.57450 0.05070
Kenya 2012 0.84783 0.70000 0.37030 0.22130 0.69920 0.02720
Kenya 2012 0.87000 0.65000 0.00100 0.22430 1.77430 0.04110
Kenya 2012 0.65217 0.47000 0.35590 0.12330 2.00320 0.10560
249
Kenya 2012 0.54000 0.42000 0.00970 0.09340 0.61440 0.15390
Kenya 2012 0.73913 0.56000 0.30810 0.07460 0.65540 0.01020
Kenya 2012 0.69565 0.55000 0.15207 0.10920 1.32330 0.02040
Kenya 2012 0.60000 0.44000 0.24587 0.01730 0.92570 0.13210
Kenya 2012 0.78000 0.55000 0.23061 0.15200 1.04930 0.04030
Kenya 2012 0.73913 0.60000 0.61909 0.10470 1.11660 0.03150
Kenya 2012 0.69565 0.60000 0.40000 0.24430 0.96130 0.06480
Kenya 2012 0.80435 0.64000 0.21813 0.06470 1.09530 0.03310
Kenya 2012 0.70000 0.56000 0.14482 0.08400 0.91630 0.04010
Kenya 2012 0.80435 0.65000 0.37670 0.16150 1.04880 0.04250
Kenya 2012 0.82609 0.70000 0.10000 0.19790 1.21450 0.05780
Kenya 2012 0.69565 0.60000 0.30000 0.21170 1.11690 0.02430
Kenya 2012 0.63043 0.46000 0.40000 0.05540 0.78660 0.02930
Kenya 2012 0.89130 0.70000 0.07950 0.49220 3.58760 0.05270
Kenya 2012 0.80435 0.70000 0.15350 0.25330 2.68940 0.02000
Kenya 2012 0.69565 0.46000 0.74560 0.25160 1.38090 0.03310
250
Kenya 2012 0.80000 0.60000 0.37730 0.30700 0.83710 0.03110
Kenya 2012 0.62000 0.46000 0.33210 0.06900 1.31620 0.10045
Kenya 2012 0.76087 0.56000 0.68260 0.23350 1.55750 0.02390
Kenya 2012 0.84783 0.70000 0.12420 0.59770 1.84310 0.01200
Kenya 2012 0.78261 0.55000 0.51760 0.15050 0.92570 0.03300
Kenya 2012 0.84783 0.60000 0.62900 0.29710 1.10220 0.03830
Kenya 2012 0.78000 0.55000 1.10810 0.20720 0.90570 0.01760
Kenya 2012 0.60870 0.48000 1.04360 0.08390 0.68570 0.04330
Kenya 2012 0.65000 0.45000 0.13925 0.13140 1.41290 0.12000
Kenya 2012 0.60870 0.41000 0.00950 0.00520 0.69760 0.10200
Kenya 2012 0.67391 0.42000 0.06023 0.04650 0.64320 0.03920
Kenya 2012 0.60870 0.44000 0.14894 0.09400 1.04940 0.00830
Kenya 2012 0.84783 0.68000 1.68450 0.34760 0.70050 0.02360
Kenya 2012 0.69565 0.62000 0.20368 0.20130 1.07500 0.01210
Kenya 2012 0.85000 0.68000 0.08152 0.53629 0.88267 0.01760
Kenya 2012 0.73913 0.55000 0.15740 0.23130 1.24520 0.05780
251
Kenya 2012 0.89130 0.70000 0.14320 0.42100 3.78080 0.03130
Kenya 2012 0.80435 0.65000 0.06100 0.33230 2.28910 0.06300
Kenya 2012 0.84783 0.68000 0.24370 0.60180 3.12890 0.07450
Kenya 2012 0.60870 0.48000 0.46600 0.13660 0.76680 0.05090
Kenya 2012 0.69565 0.48000 0.48980 0.20860 0.52650 0.03900
Kenya 2012 0.89130 0.70000 0.24840 0.33380 1.45450 0.06230
Uganda 2012 0.63043 0.50000 0.18966 0.01830 1.47800 0.14680
Uganda 2012 0.65217 0.44000 0.49190 -0.02710 0.89070 0.04970
Uganda 2012 0.60870 0.50000 0.07163 0.07970 1.20100 0.13968
Uganda 2012 0.60870 0.44000 0.08090 0.07910 0.91150 0.04250
Uganda 2012 0.60870 0.46000 0.11074 0.01500 1.16230 0.03850
Uganda 2012 0.59000 0.40000 0.30000 0.07470 1.11310 0.14470
Tanzania 2012 0.69565 0.56000 0.09000 0.21631 1.00297 0.10358
Tanzania 2012 0.63043 0.50000 0.47000 0.05698 1.12271 0.01432
Tanzania 2012 0.90000 0.70000 0.11897 0.52383 1.03036 0.03395
Tanzania 2012 0.89130 0.64000 0.13365 0.49526 1.28624 0.11302
252
Tanzania 2012 0.89130 0.62000 0.51666 0.40448 1.69233 0.04865
Rwanda 2012 0.73913 0.56000 0.01510 0.34230 2.94470 0.01640
Rwanda 2012 0.54348 0.45000 0.30000 0.06960 1.07330 0.14800
Kenya 2013 0.61000 0.45000 0.17070 0.13070 0.71970 0.15750
Kenya 2013 0.63043 0.47000 0.27760 0.19000 0.67510 0.01350
Kenya 2013 0.84783 0.70000 0.26910 0.21050 1.54270 0.02240
Kenya 2013 0.87000 0.65000 0.01000 0.23300 0.78240 0.03110
Kenya 2013 0.65217 0.47000 0.47150 0.12330 1.16500 0.10000
Kenya 2013 0.54000 0.42000 0.05670 -0.44040 0.78770 0.12940
Kenya 2013 0.73913 0.56000 0.23880 0.07460 0.66790 0.05000
Kenya 2013 0.69565 0.55000 0.09604 0.10920 1.30580 0.01460
Kenya 2013 0.60000 0.44000 0.18034 0.01730 1.01090 0.11600
Kenya 2013 0.78000 0.55000 0.27494 0.15200 1.12800 0.02710
Kenya 2013 0.73913 0.60000 0.51859 0.10470 1.22430 0.02280
Kenya 2013 0.69565 0.60000 0.40000 0.26250 1.10670 0.04730
Kenya 2013 0.80435 0.64000 0.18341 0.06470 1.19870 0.01880
253
Kenya 2013 0.70000 0.56000 0.22382 0.08400 0.95850 0.02000
Kenya 2013 0.80435 0.65000 0.47246 0.16150 1.12400 0.04450
Kenya 2013 0.82609 0.70000 0.10000 0.19790 1.26220 0.06000
Kenya 2013 0.69565 0.60000 0.30000 0.21170 1.16350 0.01340
Kenya 2013 0.63043 0.46000 0.83195 -0.15860 0.90520 0.01270
Kenya 2013 0.89130 0.70000 0.05560 0.49220 4.59060 0.03960
Kenya 2013 0.80435 0.70000 0.17710 0.16040 1.77440 0.02000
Kenya 2013 0.69565 0.46000 0.50760 0.28780 1.02340 0.02990
Kenya 2013 0.80000 0.60000 0.26950 0.30420 0.83110 0.02810
Kenya 2013 0.62000 0.46000 0.32740 0.06900 1.40140 0.01030
Kenya 2013 0.76087 0.56000 0.40760 0.25170 2.22710 0.01560
Kenya 2013 0.84783 0.70000 0.11290 0.59770 1.90440 0.01010
Kenya 2013 0.78261 0.55000 0.50420 0.15050 1.14190 0.01810
Kenya 2013 0.84783 0.60000 0.51230 0.29710 1.17230 0.02820
Kenya 2013 0.78000 0.55000 0.67990 0.20720 0.94540 0.02000
Kenya 2013 0.60870 0.48000 1.10230 0.08390 0.76500 0.02870
254
Kenya 2013 0.65000 0.45000 0.10750 0.13140 1.28630 0.12000
Kenya 2013 0.60870 0.41000 0.00950 0.00520 0.88830 0.02000
Kenya 2013 0.67391 0.42000 0.07263 0.04650 1.00900 0.01430
Kenya 2013 0.60870 0.44000 0.11259 0.09400 1.08460 0.00530
Kenya 2013 0.84783 0.68000 1.51510 0.43160 0.74940 0.02460
Kenya 2013 0.69565 0.62000 0.20368 0.32020 1.25060 0.00800
Kenya 2013 0.85000 0.68000 0.04679 0.52410 1.43862 0.02000
Kenya 2013 0.73913 0.55000 0.10190 0.19180 1.13850 0.05360
Kenya 2013 0.89130 0.70000 0.26170 0.42100 4.08650 0.02780
Kenya 2013 0.80435 0.65000 0.04470 0.33230 0.92090 0.10220
Kenya 2013 0.84783 0.68000 0.08530 0.60180 4.77230 0.05970
Kenya 2013 0.60870 0.48000 0.38690 0.13660 0.69350 0.01180
Kenya 2013 0.69565 0.48000 0.61970 0.21770 0.62230 0.02400
Kenya 2013 0.89130 0.70000 0.23670 0.33380 3.74520 0.03360
Uganda 2013 0.63043 0.50000 0.00822 0.01830 1.88130 0.04030
Uganda 2013 0.65217 0.44000 0.49190 -0.02710 0.85940 0.03990
255
Uganda 2013 0.60870 0.50000 0.06297 0.07970 1.34870 0.02133
Uganda 2013 0.60870 0.44000 0.08090 0.07910 0.93550 0.10468
Uganda 2013 0.60870 0.46000 0.62314 0.01500 1.17110 0.13750
Uganda 2013 0.59000 0.40000 0.30000 0.07470 1.11020 0.13730
Tanzania 2013 0.69565 0.56000 0.09000 0.20849 1.06570 0.03354
Tanzania 2013 0.63043 0.50000 0.47000 0.05698 1.35944 0.01039
Tanzania 2013 0.90000 0.70000 0.11897 0.52383 0.80362 0.02423
Tanzania 2013 0.89130 0.64000 0.13365 0.49526 1.23330 0.09213
Tanzania 2013 0.89130 0.62000 0.51666 0.40448 2.52512 0.03878
Rwanda 2013 0.73913 0.56000 0.01510 0.34230 1.32940 0.00980
Rwanda 2013 0.54348 0.45000 0.30000 0.06960 1.21170 0.12880