Abstract
This study mainly examined the effect of Corporate governance on the performance of deposit money banks in Sub Saharan Africa (SSA). Specifically, the effect of appointment of more non- executive directors-BNEDDUM on return on assets (ROA) and net interest margin (NIM) of the banks in SSA was determined. Conversely, the work examined the effect of appointment of more executive directors on the ROA and NIM of the banks. Secondary data on six SSA countries and twelve banks collected for the period 2004 to 2016 were used. Panel data regression approach was employed to analyze the data. Fixed effects and Random effects models were adopted based on the results of Hausman tests. The study revealed among others that appointment of more number of non-executive directors has a positive but insignificant effect on ROA. It also indicated a strong positive correlation with both ROA and NIM. A hypothetical appointment of more executive directors showed a positive and significant effect on NIM while indicating the negative and insignificant effect on ROA. The positive effect of BNEDDUM on ROA coupled with its strong positive correlation with ROA and NIM seem to strongly suggest that appointment of more non-executive directors in deposit money banks in SSA is more beneficial to the banks than the appointment of more executive directors. However, the global conflict in the findings associated with appointment of directors is not yet fully resolved. The study recommends that while more non-executive directors may be appointed, banks in SSA must put in place internal control systems which promote a culture of professionalism in management.
Keywords: Randomized experiment, Professionalism, Internal control systems, Non-executive director, Executive director, Causality, Innovation, Banks’ performance.
Received: 5 November 2018 / Revised: 12 December 2018 / Accepted: 17 January 2019/ Published: 8 March 2019
Contribution/ Originality
This study originates a new approach to attempt to resolve the challenge of causality in the relationship between corporate governance and firm performance by improvising a randomized experiment which made it possible to examine two sets of firms-one which appointed more non-executive directors and another that appointed more executive directors.
1. INTRODUCTION
The banking system is the engine of growth in any economy given its functions of financial intermediation, provision of an efficient payment system and facilitating the implementation of monetary policies (Nwaubani and Ezeudu, 2015). This fact is also acknowledged by Ogunbiyi and Ihejirika (2014) who describe banking as an economic activity which deals with the intermediation of funds between the surplus units and the deficit units of an economy and the channeling of such resources to profitable investments. Moyo et al. (2014) see the banking industry from its essential role of resource mobilization and allocation in an economy and, its position as the most important segment of the financial system in developing economies.
The genesis of banking in Sub Saharan Africa dates back to pre-colonial days and spans mainly through the era dominated by foreign-owned banks at the time of independence of African nations, the phase of government intervention/state-owned banks and the era of banking crises in the 1980s and 1990s. The banking crises era of the 1980s and 1990s is followed by the period of financial liberalization/reforms, increased private sector participation and entry of foreign banks (Beck et al., 2014; Otchere and Senbet, 2017). Another important phase is the emergence of African banks by origin which has engaged in significant cross-border expansion within the African continent (Mecagni et al., 2015).
Globally, business entities do not operate in isolation. They are an integral part of and influenced by the environment they operate in. The environment could be broadly categorized into internal and external. The internal environment at its simplest level refers to all the factors which are specific to a particular organization and influence the operations and performance of the organization. The internal environment of the banking industry in Sub Saharan Africa (SSA) over the recent decades has been very dynamic, increasingly complex and challenging particularly with the influence of globalization. The phenomenon has put deposit money banks under increasing pressure to adjust their internal environment in order to survive and remain relevant in the industry.
One of the crucial factors of the internal environment is corporate governance which is defined as the structures and processes by which companies are directed and controlled (International Finance Corporation (IFC), 2016). Virtually all countries in SSA have on the form of corporate governance code or the other. For instance, in Nigeria, a harmonized and unified national code of corporate governance for private was released in 2016 by the Financial Reporting Council of Nigeria. The code which supersedes the Central Bank of Nigeria 2014 reviewed Corporate Governance Code for Banks and Discount Houses specifies among other numerous requirements that more number of non-executive directors than executive directors shall be appointed on the board of directors of a public or private company in Nigeria inclusive of deposit money banks (https//:www.proshareng.com/admin/upload/reports/PrivateSectorCode.pdf, www.com/banking.../cbn).
Specifically, the code requires that not less than two-thirds of the total number of directors on the board shall be non-executive directors. It may be noted that Nigeria had earlier introduced a corporate governance code in 2006 for banks as part of the major financial and banking reforms implemented in 2005 (www.ecgi.org/codes/.../cgcode nigeria).
The issue of corporate governance has in recent years become a topical one among policymakers and other various stakeholders particularly in emerging and developing markets. Poor corporate governance has been linked to some notable corporate failures and financial scandals in the recent past such as the collapse of Enron, Worldcom, Tyco and Xerox in the United States of America and most bank distress and failures in Nigeria and elsewhere in the World (Akingunola et al., 2013; Gyamerah and Agyei, 2016).
1.1. Objective of the Study
The main purpose of this study is to determine the effect of appointment of directors on the performance of deposit money banks in Sub Saharan Africa (SSA). Specific objectives are an examination of:
(i) The effect of appointment of more non-executive directors than executive directors to the board on return on assets (ROA) of deposit money banks in SSA
(ii) The effect of appointment of more executive directors than non-executive to the board on ROA of deposit money banks in SSA
(iii) The effect of a appointment of more non-executive directors than executive directors to the board on net interest margin (NIM) of deposit money banks in SSA
(iv) The effect of appointment of more executive directors than non-executive to the board on NIM of deposit money banks in SSA.
Four hypotheses were formulated in a null form and tested at 95% confidence level as stated below:
Ho1: Appointment of more non-executive directors than executive directors to the board has no
Significant effect on ROA of deposit money banks in SSA.
Ho2: Appointment of more executive directors than non-executive directors to the board has no
Significant effect on ROA of deposit money banks in SSA.
Ho3: Appointment of more non-executive directors than executive directors to the board has no
Significant effect on NIM of deposit money banks in SSA.
Ho4: Appointment of more executive directors than non-executive directors to the board has no
Significant effect on NIM of deposit money banks in SSA.
1.2. Statement of the Problem
A number of empirical studies on corporate governance and performance of banks have been carried out. However, empirical studies which considered corporate governance as one of the internal factors influencing the profitability of deposit money banks in the SSA as a region are scanty (Flamini et al., 2009). Also, only a few empirical works not even on SSA as a region but on individual countries of SSA (Kyereboah-Coleman and Biekpe, 2008; John, 2015; Atuahene, 2016; Dauda and Hawa, 2016) captured appointment of directors as one of the explanatory variables in their models. In this study, a crucial aspect of corporate governance which is the appointment of directors is considered. The corporate governance codes for the banking industry in most SSA countries including Nigeria specify that number of non-executive directors shall be appointed to the board of directors of a firm than executive directors. Though non-executive directors may provide a balancing influence and help to minimize conflicts of interest among members of the Board and Management staff of a bank, there have been conflicting findings globally on the benefit of appointing more non-executive directors than executive directors on a board of directors of a deposit money bank (as required by most SSA countries’ corporate governance codes). While Black (2001); El Mehdi (2007); Wahab et al. (2007); Atuahene (2016) and Dauda and Hawa (2016) documented a positive relationship between performance and appointment of more non-executive directors; Bhagat and Black (2002); Kyereboah-Coleman and Biekpe (2008); Al-Baidhani (2013); John (2015) and Yilmaz and Buyuklu (2016) reported negative outcomes. The motivation for this study is therefore, a desire to enrich empirical studies on corporate governance in SSA particularly with respect to the appointment of directors and to attempt to resolve the documented conflict in findings.
2. THE CONCEPT OF CORPORATE GOVERNANCE
Corporate governance according to IFC (2016) is defined as the structures and processes by which companies are directed and controlled. Going further, the Corporation notes that good corporate governance leads to the efficient performance of companies, improved access to capital and serves as risk mitigant and a check on mismanagement resulting in more accountability and transparency to all stakeholders. The author adds that African countries have joined the global drive for greater transparency and accountability. Perhaps this informs the position of World Bank that good corporate governance enhances firms’ performance and access to capital (World Bank, 2005). A broader approach to corporate governance is adopted by King III Committee on Corporate Governance for South Africa in which the legitimate interests and expectations of all stakeholders apart from shareholders are considered and recognized in board decisions in order to promote sustainability of the organization (KPMG, 2014).
Corporate governance can also be viewed from a border perspective as the processes and structures by which organizations are directed and controlled so that they will operate in a responsible, fair and transparent manner to all stakeholders while being held accountable in order to serve and sustain the interests and expectations of the stakeholders.
Ordinarily, the structures and processes by which companies are directed and controlled are primarily internal to a firm. However, as part of the government responsibility to provide legislation and regulations to ensure that the business entities adopt best practices and operate in a manner that protects the interests of all stakeholders, codes of corporate governance have been introduced for adoption by organizations. This cuts across the globe.
The necessity of adoption of the corporate governance codes for banks in Sub Saharan Africa stems particularly from the gross mismanagement hitherto witnessed in the region's banking sector particularly between the 1980s and 1990s. The mismanagement was fueled by technical and managerial incompetence and unethical practices which are some of the key issues being addressed by the corporate governance codes. This opinion agrees with the view of Akingunola et al. (2013) who linked the bank distress in Nigeria in the 1990s to the failure of professional ethics which manifested in such acts as creative accounting practices, disregard to internal control systems among others.
Corporate governance in SSA has been on the fore burner through the activities of African Corporate Governance Network (ACGN) and African Corporate Governance Programme (AFCGP) supported by IFC (2016). As reported by Klynveld Peat Marwick Goerdeler (2017) a number of countries in SSA have adopted corporate governance code of practice or its equivalent, with most countries adopting their first codes from 2000 onwards. The report reveals that corporate governance requirements for listed companies in 15 countries across Africa meet Principles of Corporate Governance released in 2015 by the Organization for Economic Co-operation and Development ( OECD). The principles include: leadership and culture, strategy and performance, compliance and oversight, and stakeholder engagement.
As documented in the report, South Africa ranks first in Africa while Kenya, Mauritius, Nigeria and Uganda are in the top five. The African Corporate Governance Network (ACGN) is a collaborative network of directors of organizations which is engaged in promoting effective and inclusive corporate governance in Africa (African Corporate Governance Network (ACGN), 2016). By 2015 the ACGN had a membership strength of about 16 countries of Africa and 7 affiliate members with most of the members coming from Sub Saharan Africa (www.afcgn.org).
According to the ACGN, the state of corporate governance in 11 Sub Saharan African (SSA) countries in 2015 is presented in Table 1.
It may be noted that some of the reviewed countries have issued new codes to further improve their corporate governance practices after the review exercise by ACGN (2016). For instance, in 2016 Kenya, Mauritius and Nigeria issued new codes in pursuance of the drive for improved corporate governance in Sub Saharan Africa. Specifically, the Capital Market Authority in Kenya issued a new code in 2016 titled “Code of Corporate Governance for Issuers of Securities to the Public 2016 ” (Mulenwa Wordpress, 2016) while Mauritius did the same through the National Committee on Corporate Governance (Financial Services Commission Circular Letter- FSC, 2018). The new code is captioned “National Code of Corporate Governance 2016.” On the other hand, Nigeria took time to harmonize and unify her codes for a number of major sectors in the economy (Proshare, 2016). The unified code issued by the Financial Reporting Council of Nigeria is titled "National Code of Corporate Governance 2016."
Table 1 suggests that SSA countries are making progress in the area of adopting best corporate governance codes. However, notwithstanding the progress in the issuance and adoption of the relevant corporate governance code in each country in SSA region, it seems appropriate to stress the need for effective internal control systems, integrity, professionalism, technical competency and commitment of the members of the board of directors of each firm. This caution aligns with the view of FBN (2015) that “Effective corporate governance practices are largely dependent on the skills, integrity and experience of individuals on the Board and how well they are committed to doing business in accordance with global best practices”
Table-1. Corporate Governance Codes in 11 Sub Saharan African Countries Reviewed by ACGN in 2015.
| Country | Corporate Governance Codes, Principles Guidelines and Regulations (excluding primary Legislations) | Date Issued | Issuing Body | *Remark/2016 Code Issued |
| 1.Ghana |
|
2002 2015 2011 | Securities & Exchange Comm. Public Service Com Bank of Ghana |
|
| 2.Kenya |
|
2015
2014
2002 2012 2011 |
Capital Market Authority
-do-
Central bank of Kenya Insurance Reg. Auth |
Code of Corp Gov for issuers of securities to the public 2016 |
| 3.Malawi |
|
2010
2011 2010 |
Inst. of Directors, Malawi Nat. Corp Gov Reviewed Committee. Rsv Bank of Malawi | |
| 4.Mauritius |
|
2014 2004 2007 2014 |
Nat. Committee on Corp Governance Bank of Mauritius |
Nat. Code of Corp Gov 2016 |
| 5.Mozambique |
|
2011 | Inst. of Directors | |
| 6.Nigeria |
|
2015
2014 2014 2011 2009 2008 |
Financial Reporting Council The Nig Telecom Commission Central Bank of Nig Nig Insurance Com Nig Pensions Com |
Nat. Code of Corp Gov 2016 |
| 7.South Africa |
|
2009
2012
2003 2014 2012 |
King Committee, Inst. of Directors Inst. of Directors in Southern Africa Dept. of Pub. Entp Fin Services Board South African Rsv Bank |
|
| 8.Tanzania |
|
2008 2002 |
Bank of Tanzania Cap. Market & Securities Auth. |
|
| 9.Uganda |
|
2005 2003 2002 | Central Bank of Uganda Central Market Auth Inst. of Corp Gov. |
|
| 10.Zambia |
|
2008 2008 2006 2005 |
Inst. of Directors
Bank of Zambia Lusaka Stock Exch |
|
| 11.Zimbabwe |
|
2010 2004 | Min of State Entps & Parastatals Reserve Bank of Zimbabwe |
Source: ACGN (2016) * Column was added by Researcher.
3. THE IMPORTANCE OF BOARD COMPOSITION: THE THEORETICAL FRAMEWORK
Board composition is very crucial to the success and survival of a firm particularly a deposit money bank because it is the board members who collectively formulate and implement policies of the bank on behalf of the owners of the business - shareholders. As FBN (2015) acknowledges “good governance practices are best initiated and observed in the boardroom”.
An ineffective policy will ordinarily produce at best a less desirable result and an effective policy poorly implemented will not give the desired outcome.
The real issues associated with the appointment of directors are the problem of conflicting interests among the directors and managers as agents of the shareholders against the interest of the shareholders- their principal. This conflict is known as the agency problem which necessitates agency costs to the organization. The agency problem tends to hinder objective decisions which are in the best interest of the shareholders and other stakeholders for reasons which weigh more on personal interests of the agents. The agency problems are encapsulated in the agency theory which in turn is rooted in the firm theory.
The agency theory credited to Stephen Ross and Mitnick (2006) is concerned with the nature of the principal-agent relationship, the rights and responsibilities of each party, the agency problems and how to minimize them via various corporate governance practices and observations aimed at controlling decisions and actions of the agent's in the modern firm. Agency theory can be considered as one of the oldest theory in the literature of management and economics (Wasserman, 2006).
On the other hand, the firm theory could be viewed as consisting a number of economic theories that explain and predict the nature of the firm, its existence, behavior, structure, and relationship with all stakeholders and the market (Wikipedia, 2018). The neo-classical or traditional firm is a single business entity whose entire operations are carried out by an entrepreneur with the main objective of profit maximization (Jhingan and Stephen, 2009). It considers the sole objective of a firm to be profit maximization and measures profit as the difference between a firm’s total revenue and total cost and asserts that in order to maximize profit, the firm is expected to maximize its revenues and minimize or stabilize its costs. However, the authors recognize that modern firms have varied objectives because of the complexities, politics and separation of ownership from management which characterize them. They note that modern firms are run by managers/directors while shareholders are the owners with separate roles and motives from those of the managers. These facts render the sole objective of profit maximization of the traditional firm unrealistic as the modern firm has varied objectives.
In 1964 Robin Marris developed a dynamic balanced growth maximizing managerial model of the firm in recognition of the varied interests of the managers and shareholders (Marris, 1964). Marris suggests that managers/directors are usually more concerned with salary, prestige, status, power, job security while shareholders are more interested in profits, market share and output (http://www.economicsdiscussion.net/firm/top-3-theories-of-firm-with-diagram). This tendency introduces the conflict of interests which implies that the directors/managers may not act in the interest of the shareholders who bear the risk of the decisions of the executive directors and managers. The need therefore, to monitor the interests/activities of the executive directors and managers had long been identified. According to Fama and Jensen (1983) this need underscores the desire for the appointment of outside/independent directors in the board. The view of the two erudite scholars is that appointment of the outside/non-executive directors would help to control the decisions of the executive directors and align them to the interest of risk-bearers- the shareholders. This conflict of interests is known as the agency problem and was as far back as 1776 noted by Adam Smith (Panda and Leepsa, 2017).
It is therefore very imperative for not only organizations but governments to take well-thought-out steps to checkmate this necessary evil called agency problem. The corporate governance code in most countries specifies that number of non-executive directors shall be appointed on the board of directors of a firm as a way of minimizing the agent problem. Generally, corporate governance code and specific regulatory directives on board composition are part of the attempt at minimizing the problem of conflict of interests in organizations. It is assumed by the policymakers and governments -regulators and supervisors that non- executive directors particularly independent non- executive directors are more objective since they are independent and are not in full-time employment of the organization concerned. The humble opinion of the researcher is that the non-executive directors may not be actually independent as their appointment may be directly or indirectly sponsored by the executive directors whose personal interests the non-executive directors may not like to betray.
4. SUMMARIZED EMPIRICAL REVIEW
Empirical works which documented a general positive-performance link outcomes are: Black (2001)-Russia; El Mehdi (2007)-Tunisia; Wahab et al. (2007)-Malaysia; Brown and Caylor (2004)-USA and particularly in Chepkosgei (2013)-Kenya, Dauda and Hawa (2016)-Nigeria, Atuahene (2016)-Ghana and in Herdjiono and Sari (2017)-Indonesia where board of directors with more number of independent/non-executive directors - BNEDDUM indicated a positive relationship with ROA (Duada and Hawa) and positive effect on ROA ( Chepkosgei; Atuahene; Herdjiono and Sari). On the other hand, empirical studies which indicated generally negative outcomes are: Bhagat and Black (2002); Kyereboah-Coleman and Biekpe (2008)-Ghana; Al-Baidhani (2013)-Arabian Penisula, John (2015)-Nigeria, Yilmaz and Buyuklu (2016)-Turkey where independent directors/ non-executive directors board had a negative and significant effect on ROA (Al-Baidhani); also where it exhibited a negative relationship (Bhagat and Black; Yilmaz and Buyuklu; John).
5. RESEARCH METHODOLOGY
The research design adopted in this work is ex-post facto. Secondary data from 12 deposit money banks selected from 6 Sub Saharan African countries of Nigeria, South Africa, Ghana, Kenya, Mauritius and Botswana were collected for the period 2004 -2006. The banks are: Guaranty TrustBank, First Bank, Zenith Bank and Access Bank for Nigeria; Standard Bank and Nedbank for South Africa: Kenya Commercial Bank and Equity Bank for Kenya; Mauritius Commercial Bank and SBM Bank for Mauritius; Standard Chartered Bank of Ghana for Ghana and Barclays Bank of Botswana for Botswana. Panel data multiple regression approach was employed to analyze the data with the aid of EViews 9 and SPSS (20). The dependent variables used in this study are bank-level factors and they are Return on Assets (ROA) to proxy profitability and Net Interest Margin (NIM) to measure efficiency. The independent variable is board composition innovatively divided into: BNEDDUM - a dummy to reflect if number of none-executive directors is more than those of executive director on the Board of each bank and BMEDDUM – a dummy to reflect a hypothetical board of directors composition with 61% of the directors as Executive Directors innovatively introduced by the researcher. The final model is a modified version of the models adopted by Atuahene (2016) and Flamini et al. (2009) and it is given as:
ROAic,t/NIMic,t = α +∑ β1BNEDDUM ic,t +∑β2BMEDDU ict + Vi,t (1)
Where:
ROAic,t is the return on total assets of bank i in country c for period t;
NIMic,t is the net interest margin of bank i in country c for period t.
BNEDDUM ic,t / BMEDDUM ict is the board composition of bank i in country c for period t,
α is the constant for the model
β1 to β2 are parameters/ beta coefficients to be estimated
νit= uit + εit is the composite disturbance factor, while uit = between-entity errors and εit = within-entity errors (the idiosyncratic errors).
ROA is employed in this study (as also used in Yesmine and Bhuiyah (2015); Mungly et al. (2016) and Iacobelli (2017) and is preferred to the average-assets values of return on average assets (ROAA). This is because between ROAA and ROA, ROAA is often expected to give higher profitability since it uses average assets which usually are lower than gross assets. The emphasis here is on profitability and the researcher’s view is that a conservative approach which yields less profitability appears preferable. The choice of ROAA approach is usually anchored on the argument that it avoids (smoothens out) the effects of extreme-year-end values of assets such as possible use of window dressing techniques (Perera et al., 2013). However, the avoidance of the extreme (usually) higher values tends to result in higher profitability ratios which may be misleading. In view of this, ROA which gives lower ratios under extreme high values appears preferable.
5.1. Methods of Data Analysis
Panel data multiple regression approach is employed to analyze the panel data under random effects and fixed effects models with the aid of Eviews 8 while SPSS (20) is used for production of relevant supporting graphs and generation of multivariate correlations. The use of fixed or random effects model for each variable is dictated by the result of Hausman test. The random effects model is adopted when it appears that the error terms (unique errors) are not correlated with the explanatory variables (Torres-Reyna, 2007). This is determined via the Hausman test. The null hypothesis in the Hausman test is that the preferred model is random effects model otherwise, fixed effects is the preferred model. The null hypothesis (random effects model) is rejected and the fixed effects model accepted if the resulting p-value from the test is less than the selected level of significance.
6. DATA PRESENTATION AND ANALYSIS
Figures 1 and 2 below indicate that the variables fluctuated within the period of the study. The fluctuations reflect changes in board appointment, economic situations and market structures particularly with respect to net interest margins (green color- Figure 1). The trend of the net interest margin (NIM) shown above particularly as exhibited by Figure 2 reflects some extreme NIM values recorded by some of the selected banks for this study. For instance, within the period, First Bank Nigeria recorded the highest NIM of 86.32% in 2014 suggestively following risk assets restructuring which might has resulted in lower loan value. Also, Standard Chartered Bank of Ghana documented a NIM of 36.45% in 2016- the highest in the year among the banks. The extreme values combined to generate the maximum average value of 42%- considered too high.
Figure-1. Trend of the Variables within the Period,2004-2016.
Source: SPSS(20) output, 2018.
Figure-2. Trend of the Variables within the Period, 2004-2016 in Categorical Graph.
Source: Eviews 9 Output 2018.
According to Pelaelo (2017) net interest margin may be considered as an indicator of the level of competition in the market and by extension is linked to the level of financial system development. The data for this study revealed that while Standard Bank and Nedbank both of South Africa and Mauritius Commercial Bank and SBM Bank also of Mauritius record one digit NIMs, the NIMs figures for all the other selected banks in Nigeria, Ghana, Kenya and Botswana are in two digits. Logically, these NIM figures suggest that competition and financial system development are more enhanced in South Africa and Mauritius compared to the other selected countries within the period of the study.
6.1. Results of the Panel Data Regression Analysis
Table-2. Correlation Among the Variables.
Correlations
ROA |
NIM |
BNEDDUM |
BMEDDUM |
||
ROA |
Pearson Correlation |
1 |
.521** |
.209** |
-0.043 |
Sig. (2-tailed) |
0 |
0.009 |
0.598 |
||
N |
156 |
156 |
156 |
156 |
|
NIM |
Pearson Correlation |
.521** |
1 |
.238** |
0.122 |
Sig. (2-tailed) |
0 |
0.003 |
0.128 |
||
N |
156 |
156 |
156 |
156 |
|
BNEDDUM |
Pearson Correlation |
.209** |
.238** |
1 |
-.227** |
Sig. (2-tailed) |
0.009 |
0.003 |
0.004 |
||
N |
156 |
156 |
156 |
156 |
|
BMEDDUM |
Pearson Correlation |
-0.043 |
0.122 |
-.227** |
1 |
Sig. (2-tailed) |
0.598 |
0.128 |
0.004 |
||
N |
156 |
156 |
156 |
156 |
|
**. Correlation is significant at the 0.01 level (2-tailed).
Source: SPSS(20) Output 2018.
Note: ROA►Return on Assets, NIM►Net interest Income, BNEDDUM►Dummy for Non-Executive Directoors, BMEDDUM►Dummy for Executive Directors.
The Table 2 above which indicates the correlation among the variables was generated to assist in driving discussion of findings under Section 7 below. The Table is fully discussed under the Section 7.
Table-3a. Panel Data Regression Result (Fixed Effects Model) for Hypotheses 1 & 2 – ROA.
Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
||
C |
1.581179 |
0.348354 |
4.539003 |
0 |
||
CAPADQ |
0.007704 |
0.009029 |
0.853226 |
0.395 |
||
EMPPROD |
0.504368 |
0.087755 |
5.747474 |
0 |
||
STAFTBFT |
0.01002 |
0.015476 |
0.647407 |
0.5184 |
||
BNEDDUM |
0.079961 |
0.530992 |
0.150588 |
0.8805 |
||
BMEDDUM |
-0.094849 |
0.157046 |
-0.60396 |
0.5469 |
||
Effects Specification |
||||||
Cross-section fixed (dummy variables) |
||||||
R-squared |
0.760229 |
Mean dependent var |
3.144103 |
|||
Adjusted R-squared |
0.732629 |
S.D. dependent var |
1.712456 |
|||
S.E. of regression |
0.885475 |
Akaike info criterion |
2.697182 |
|||
Sum squared resid |
108.9852 |
Schwarz criterion |
3.029538 |
|||
Log likelihood |
-193.3802 |
Hannan-Quinn criter. |
2.832171 |
|||
F-statistic |
27.54497 |
Durbin-Watson stat |
1.139702 |
|||
Prob(F-statistic) |
0 |
|||||
Note: FIXED EFFECTS MODEL-ROA: Hypothesis 1 & 2 and Dependent Variable is ROA.
Table 3a below exhibits the result of the panel data regression analysis on ROA based on fixed effect model. The decision on this result would be taken after the random effects model specification and Hausman test have been carried out.
Table 3b below shows the result of the panel data regression analysis on ROA based on random effect model. The final decision on this result would depend on the outcome of a Hausman test which would be carried out.
Table-3b. Panel Data Regression Result (Random Effects Model) for Hypotheses 1 & 2 - ROA contd.
Dependent Variable: ROA
Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
||
C |
1.682447 |
0.549009 |
3.064517 |
0.0026 |
||
CAPADQ |
0.008789 |
0.008979 |
0.978772 |
0.3293 |
||
EMPPROD |
0.464054 |
0.082951 |
5.594314 |
0 |
||
STAFTBFT |
0.008324 |
0.015328 |
0.543069 |
0.5879 |
||
BNEDDUM |
0.116264 |
0.526703 |
0.220739 |
0.8256 |
||
BMEDDUM |
-0.090283 |
0.156734 |
-0.57603 |
0.5655 |
||
Effects Specification |
||||||
S.D. |
Rho |
|||||
Cross-section random |
1.502901 |
0.7423 |
||||
Idiosyncratic random |
0.885475 |
0.2577 |
||||
Weighted Statistics |
||||||
R-squared |
0.17994 |
Mean dependent var |
0.507048 |
|||
Adjusted R-squared |
0.152604 |
S.D. dependent var |
0.965337 |
|||
S.E. of regression |
0.888632 |
Sum squared resid |
118.45 |
|||
F-statistic |
6.582667 |
Durbin-Watson stat |
1.04263 |
|||
Prob(F-statistic) |
0.000014 |
|||||
Unweighted Statistics |
||||||
R-squared |
-0.02507 |
Mean dependent var |
3.144103 |
|||
Sum squared resid |
465.92 |
Durbin-Watson stat |
0.265061 |
|||
Note: RANDOM EFFECTS MODEL-ROA: Hypothesis 1 & 2 and Dependent Variable: is ROA.
Table-3c. Panel Data Regression Result (Hausman Test) for Hypotheses 1 & 2 – ROA.
Correlated Random Effects - Hausman Test
Equation: Untitled
Test cross-section random effects
Test Summary |
Chi-Sq. Statistic |
Chi-Sq. d.f. |
Prob. |
|
Cross-section random |
6.071431 |
5 |
0.2993 |
|
Cross-section random effects test comparisons: |
||||
Variable |
Fixed |
Random |
Var(Diff.) |
Prob. |
CAPADQ |
0.007704 |
0.008789 |
0.000001 |
0.2495 |
EMPPROD |
0.504368 |
0.464054 |
0.00082 |
0.1592 |
STAFTBFT |
0.01002 |
0.008324 |
0.000005 |
0.4286 |
BNEDDUM |
0.079961 |
0.116264 |
0.004537 |
0.5899 |
BMEDDUM |
-0.09485 |
-0.09028 |
0.000098 |
0.6444 |
Cross-section random effects test equation:
Dependent Variable: ROA
Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
||
C |
1.581179 |
0.348354 |
4.539003 |
0 |
||
CAPADQ |
0.007704 |
0.009029 |
0.853226 |
0.395 |
||
EMPPROD |
0.504368 |
0.087755 |
5.747474 |
0 |
||
STAFTBFT |
0.01002 |
0.015476 |
0.647407 |
0.5184 |
||
BNEDDUM |
0.079961 |
0.530992 |
0.150588 |
0.8805 |
||
BMEDDUM |
-0.094849 |
0.157046 |
-0.60396 |
0.5469 |
||
Effects Specification |
||||||
Cross-section fixed (dummy variables) |
||||||
R-squared |
0.760229 |
Mean dependent var |
3.144103 |
|||
Adjusted R-squared |
0.732629 |
S.D. dependent var |
1.712456 |
|||
S.E. of regression |
0.885475 |
Akaike info criterion |
2.697182 |
|||
Sum squared resid |
108.9852 |
Schwarz criterion |
3.029538 |
|||
Log likelihood |
-193.3802 |
Hannan-Quinn criter. |
2.832171 |
|||
F-statistic |
27.54497 |
Durbin-Watson stat |
1.139702 |
|||
Prob(F-statistic) |
0 |
|||||
Note: HAUSMAN TEST -ROA: Hypothesis 1 & 2 and Dependent Variable: is ROA.
Source: Eviews 9 Ouput, 201.
Table 3c shows the results of the Hausman test. Details of the results constitute the findings of the study and are fully discussed under Section 7 below.
Table-4a. Panel Data Regression Result (Fixed Effects Model) For Hypotheses 3 & 4 – NIM.
Cross-section fixed (dummy variables) |
|||
R-squared |
0.589668 |
Mean dependent var |
11.6109 |
Adjusted R-squared |
0.542435 |
S.D. dependent var |
9.062517 |
S.E. of regression |
6.130208 |
Akaike info criterion |
6.566901 |
Sum squared resid |
5223.544 |
Schwarz criterion |
6.899257 |
Log likelihood |
-495.218 |
Hannan-Quinn criter. |
6.70189 |
F-statistic |
12.48436 |
Durbin-Watson stat |
2.272762 |
Prob(F-statistic) |
0 |
||
Dependent Variable: NIM
Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
C |
9.872568 |
1.651083 |
5.979449 |
0 |
CAPADQ |
-0.03318 |
0.054967 |
-0.6036 |
0.5471 |
EMPPROD |
0.759845 |
0.367423 |
2.068041 |
0.0405 |
STAFTBFT |
-0.14233 |
0.064773 |
-2.19734 |
0.0297 |
BNEDDUM |
-5.91363 |
2.224998 |
-2.65781 |
0.0088 |
BMEDDUM |
1.562918 |
0.658404 |
2.373798 |
0.019 |
Effects Specification |
||||
Cross-section fixed (dummy variables) |
||||
R-squared |
0.76417 |
Mean dependent var |
11.32641 |
|
Adjusted R-squared |
0.737024 |
S.D. dependent var |
7.206844 |
|
S.E. of regression |
3.695756 |
Akaike info criterion |
5.554814 |
|
Sum squared resid |
1898.547 |
Schwarz criterion |
5.88717 |
|
Log likelihood |
-416.276 |
Hannan-Quinn criter. |
5.689802 |
|
F-statistic |
28.15045 |
Durbin-Watson stat |
1.752502 |
|
Prob(F-statistic) |
0 |
|||
Note: FIXED EFFECTS MODEL:- NIM: Hypothesis 2& 3and Dependent Variable: is NIM.
Table 4a above exhibits result of the panel data regression analysis on ROA based on fixed effect model. The final decision on this result would be reached after the random effects model and Hausman test have been carried out.
Table-4b. Panel Data Regression Result (Random Effects Model) For Hypotheses 3 & 4 - NIM Contd.
Dependent Variable: NIM
Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
C |
9.493095 |
2.111295 |
4.496337 |
0. 0000 |
CAPADQ |
-0.01395 |
0.054152 |
-0.25763 |
0.797 |
EMPPROD |
0.75232 |
0.336284 |
2.237156 |
0.0268 |
STAFTBFT |
-0.14911 |
0.063781 |
-2.33785 |
0.0207 |
BNEDDUM |
-4.86335 |
2.195447 |
-2.2152 |
0.0283 |
BMEDDUM |
1.694256 |
0.655959 |
2.582867 |
0.0108 |
Effects Specification |
||||
S.D. |
Rho |
|||
Cross-section random |
4.907209 |
0.6381 |
||
Idiosyncratic random |
3.695756 |
0.3619 |
||
Weighted Statistics |
||||
R-squared |
0.141114 |
Mean dependent var |
2.315879 |
|
Adjusted R-squared |
0.112485 |
S.D. dependent var |
4.026475 |
|
S.E. of regression |
3.793262 |
Sum squared resid |
2158.326 |
|
F-statistic |
4.928981 |
Durbin-Watson stat |
1.541847 |
|
Prob(F-statistic) |
0.000331 |
|||
Unweighted Statistics |
||||
R-squared |
0.004297 |
Mean dependent var |
11.32641 |
|
Sum squared resid |
8015.887 |
Durbin-Watson stat |
0.415152 |
|
Note: RANDOM EFFECTS MODEL:- NIM: Hypothesis 2& 3and Dependent Variable: is NIM.
Table 4b above shows result of the panel data regression analysis on ROA based on random effect model. Final decision on this result would depend on the outcome of a Hausman test which would be carried out.
Table-4c. Panel Data Regression Result (Hausman Test) For Hypotheses 3 & 4 –NIM.
Equation: Untitled
Test cross-section random effects
Test Summary |
Chi-Sq. Statistic |
Chi-Sq. d.f. |
Prob. |
|
Cross-section random |
13.01943 |
5 |
0.0232 |
|
Cross-section random effects test comparisons: |
||||
Variable |
Fixed |
Random |
Var(Diff.) |
Prob. |
CAPADQ |
-0.03318 |
-0.01395 |
0.000089 |
0.0414 |
EMPPROD |
0.759845 |
0.75232 |
0.021912 |
0.9595 |
STAFTBFT |
-0.14233 |
-0.14911 |
0.000128 |
0.5481 |
BNEDDUM |
-5.91363 |
-4.86335 |
0.13063 |
0.0037 |
BMEDDUM |
1.562918 |
1.694256 |
0.003213 |
0.0205 |
Cross-section random effects test equation:
Dependent Variable: NIM
Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
|
C |
9.872568 |
1.651083 |
5.979449 |
0 |
|
CAPADQ |
-0.033178 |
0.054967 |
-0.6036 |
0.5471 |
|
EMPPROD |
0.759845 |
0.367423 |
2.068041 |
0.0405 |
|
STAFTBFT |
-0.142327 |
0.064773 |
-2.19734 |
0.0297 |
|
BNEDDUM |
-5.91363 |
2.224998 |
-2.65781 |
0.0088 |
|
BMEDDUM |
1.562918 |
0.658404 |
2.373798 |
0.019 |
|
Effects Specification |
|||||
Cross-section fixed (dummy variables) |
|||||
R-squared |
0.76417 |
Mean dependent var |
11.32641 |
||
Adjusted R-squared |
0.737024 |
S.D. dependent var |
7.206844 |
||
S.E. of regression |
3.695756 |
Akaike info criterion |
5.554814 |
||
Sum squared resid |
1898.547 |
Schwarz criterion |
5.88717 |
||
Log likelihood |
-416.276 |
Hannan-Quinn criter. |
5.689802 |
||
F-statistic |
28.15045 |
Durbin-Watson stat |
1.752502 |
||
Prob(F-statistic) |
0 |
||||
Note: HAUSMAN TEST:- NIM: for Hypothesis 2& 3and Dependent Variable: is NIM.
Source: Eviews 9 Output,2018.
Table 4c indicates the results of the Hausman test. Details of the results constitute the findings of the study and are fully discussed under Section 7 below.
Table-5. Summary of Random Effects and Fixed Effects Models’ Results on ROA (Hypotheses 1&2).
Fixed Effects-FE Random Effects-RE
Independent Variables |
Details in |
Beta Coef. under FE |
P-value Under FE |
Beta Coef. Under RE |
P-value Under RE |
Adopted Model basedon Hausman Test Result |
Adjustd R-Square |
F-Stat. p-value |
BNEDDUM |
Table3 |
0.079961 |
0.8805 |
0.116264 |
0.8256 |
Random Effects |
15.26% |
0 |
BMEDDUM |
-do- |
-0.094849 |
0.5469 |
-0.09028 |
0.5655 |
Random Effects |
Source: Extracted from Eview9 Results, 2018-Table 3.
Table-6. Summary of Random Effects and Fixed Effects Models’ Results on NIM(Hypotheses3&4).
Fixed Effects-FE Random Effects-RE
Independent Variables |
Details in |
Beta Coef.under FE |
P-value Under FE |
Beta Coef. Under RE |
P-value Under RE |
Adopted Model-based on Hausman Test Result |
Adjustd R-Square |
F-Stat. p-value |
BNEDDUM |
Table4 |
-5.91363 |
0.0088 |
-4.86335 |
0.0283 |
Random Effects |
10.85% |
0 |
BMEDDUM |
-do- |
1.562918 |
0.019 |
1.69456 |
0.0108 |
Random Effects |
Source: Extracted from Eview9 Results, 2018-Table 4.
7. DISCUSSION OF RESULTS
The board of directors with more number of non-executive directors than executive directors (BNEDDUM) has a positive insignificant effect on return on assets (ROA)-hypothesis1while exhibiting negative insignificant effect on net interest margin (NIM)- hypothesis 3. It also shows a positive significant correlation with both ROA and NIM (Table 2). The hypothetical board appointment (BMEDDUM) for more number of executive directors indicates the negative insignificant effect on ROA (hypothesis 2) while showing a positive significant effect on NIM (hypothesis 4). It equally exhibits negative insignificant correlation with ROA and positive insignificant relationship with NIM. The negative insignificant effect of BMEDDUM on ROA aligns with the results in Bhagat and Black (2002); Kyereboah-Coleman and Biekpe (2008); Al-Baidhani (2013); Yilmaz and Buyuklu (2016); John (2015).
The positive effect of BNEDDUM on ROA (though not significant), coupled with its positive correlation with ROA and NIM is consistent with general positive-performance link outcomes documented in Black (2001)-Russia; El Mehdi (2007)-Tunisia; Wahab et al. (2007)-Malaysia; Brown and Caylor (2004)-USA and particularly in Chepkosgei (2013)-Kenya, Dauda and Hawa (2016)-Nigeria, Atuahene (2016)-Ghana and in Herdjiono and Sari (2017)-Indonesia where appointment of more number of independent/non-executive directors - BNEDDUM indicated a positive relationship with ROA (Duada and Hawa) and positive effect on ROA ( Chepkosgei; Atuahene; Herdjiono and Sari). However, it contradicts findings in Bhagat and Black (2002); Kyereboah-Coleman and Biekpe (2008)-Ghana, Al-Baidhani (2013)-Arabian Penisula, John (2015)-Nigeria, Yilmaz and Buyuklu (2016)-Turkey where independent directors/ non-executive directors appointment had a negative and significant effect on ROA (Al-Baidhani);also where it exhibited negative correlation (Bhagat and Black; Kyereboah-Coleman, Yilmaz and Buyuklu; John).
The outcomes associated with BNEDDUM when compared with those of BMEDDUM in totality suggest that BNEDDUM is preferred to BMEDDUM. This view tends to support the regulatory requirement for the appointment of more number of non-executive directors on the board of directors of banks in many countries in Sub Saharan Africa.
According to the work of a World Bank research staff (Love, 2010) most of the studies on corporate governance and firm performance suggest a positive correlation between corporate governance and various measures of performance though a number of studies as well have questioned the relationship. The author notes that one of the challenges associated with the relationship between corporate governance and firm performance is the question of causality, in other words, does positive or negative correlation with performance imply that corporate governance causes the change in performance? Logically, if corporate governance affects performance, it implies that changes in corporate governance will produce changes in performance. This may only be true if the variation in corporate governance measure is at random and independent of other variables in the model under study. The problem of endogeneity arises when variation in corporate governance variable depends on some un-modeled causes (the error terms) which also affect other variables in the model (Antonakis et al., 2014).
An adjudged credible method of resolving this challenge is the randomized experiment in which a researcher randomly assigns some subjects to receive a treatment, while others do not receive any treatment (Love, 2010). The outcomes are compared between the two groups. In the case of governance-performance relationship research, the design would include firms as the subjects, the treatment as the changes in corporate governance and the results as performance. Because the treatment is random by design, any differences in outcome could credibly be attributed to the treatment - improvements in corporate governance. In the real world, this methodology will be very hard to implement because of practical involvements such as identifying firms willing to form a list for random selection of firms which will, in turn, form a group also willing to have some aspects of their corporate governance structures changed in the experiment. Such a change may entail dropping some executive directors for more non-executive directors or vice versa among others.
In this study, the researcher tries to be innovative by introducing a hypothetical board of directors composed of more executive directors (BMEDDUM) appointed for eight years (61%) out of the thirteen years period covered by this study. The eight years for each bank is randomly populated with ones (1s) which is the dummy for executive directors. The introduction is an attempt to improvise a mechanism mirroring the randomized experiment so that the outcome based on the non-executive directors appointment -BNEDDUM may be compared and accepted or otherwise with a level of credibility.
It appears that the introduction has added to the acceptability of the outcome with respect to the appointment of more non-executive directors (BNEDDUM). For instance, BNEDDUM indicates a positive significant relationship with both ROA and NIM Tables 5 & 6 while the introduction of BMEDDUM (more executive directors appointment) reverses the positive significant relationship to a negative insignificant correlation with ROA and positive insignificant relationship with NIM Table 6. The negative insignificant correlation of BMEDDUM with ROA seems to logically confirm the positive significant relationship of BNEDDUM with ROA. The same reasoning applies to NIM. It also suggests that the appointment of more non-executive directors enhances performance more than appointment of more executive directors.
With respect to the effect of BNEDDUM on ROA and NIM under Tables 5&6 it exhibits a positive insignificant effect on ROA and insignificant negative effect on NIM. The introduction of BMEDDUM again reverses the outcome showing a negative and insignificant effect on ROA and positive significant effect on NIM. This implies that replacing the appointment of more non-executive directors with the appointment of more executive directors will have a negative effect on profitability (ROA). The reversal tends to confirm that the appointment of more non-executive directors (BNEDDUM) actually has a positive insignificant effect on ROA. This is the essence of the introduction of the hypothetical appointment which analogically serves as a change of existing board appointments which may be very difficult to achieve in the real world.
However, when we consider the effect of the two types of appointments on NIM only, appointment of more executive directors is preferred as it exhibits a positive significant effect against the insignificant negative effect of appointment of more non-executive directors. Conversely, the board with more non-executive appears more beneficial to the deposit money banks when the effect of the two boards on ROA only is taken into account as this board indicates a positive insignificant effect against a negative and insignificant effect of the board with more executive directors. This suggests that the conflict in the findings associated with board appointments globally is not yet fully resolved. In view of this, it appears that the desired corporate governance is likely to emerge from within rather than exogenously and so be dependent on specific characteristics of each firm and its environment. This humble opinion of the researcher is consistent with the view of World Bank research staff, Love (2010).
8. CONCLUSION AND RECOMMENDATIONS
8.1. Conclusion
Appointment of more non-executives on a Board of directors of deposit money banks in SSA appears more beneficial to the banks than appointment of more executive directors. However, the conflict in the findings associated with board appointment globally is not yet fully resolved and suggests that the desired corporate governance is likely to emerge from within and be dependent on specific characteristics of each bank and its environment rather than exogenously.
8.2. Recommendations
It is recommended that while more non-executive directors than executive directors may be appointed to the Board of Directors of deposit money banks in SSA, each bank must ensure that it puts in place robust internal control systems which promote a culture of prudence and professionalism in management. Appointment of non-executive directors should be devoid of interference of the executive directors as much as possible in order to minimize the incident of conflict of interests.
| Funding: This study received no specific financial support. |
| Competing Interests: The author declares that there are no conflicts of interests regarding the publication of this paper. |
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