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No 250 March 2017
Quality of Corporate Governance on Dividend Payouts:
The Case of Nigeria
Anthonia T. Odeleye
Editorial Committee
Shimeles, Abebe (Chair) Anyanwu, John C. Faye, Issa Ngaruko, Floribert Simpasa, Anthony Salami, Adeleke O. Verdier-Chouchane, Audrey
Coordinator
Salami, Adeleke O.
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Correct citation: Odeleye, Anthonia T. (2017), Quality of Corporate Governance on Dividend Payouts: The Case of Nigeria, Working
Paper Series N° 250, African Development Bank, Abidjan, Côte d’Ivoire.
Quality of Corporate Governance on Dividend
Payouts: The Case of Nigeria a
a Anthonia T. Odeleye is a Visiting Research Fellow, Macroeconomics Policy, Forecasting and Research Department, African Development Bank, Abidjan, Cote D’Ivoire and Lecturer at Department of Economics, University of Lagos, Akoka-Lagos, Nigeria.
AFRICAN DEVELOPMENT BANK GROUP
Working Paper No. 250
March 2017
Office of the Chief Economist
Anthonia T. Odeleye
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Abstract
Corporate governance (CG) safeguards
shareholders’ portfolios and ensures optimal returns
in terms of dividend payouts (DPs) on investment.
The association between CG and DPs could be
significant in relation to risk exposure, operational
and financing activities across firms and sectors. The
relationship between CG and DPs has been well
documented, however; the role of industry
classification on the relationship has not been given
adequate consideration in the literature. This study,
therefore, examines the moderating effects of sector
classification of CG on DPs in Nigeria. Agency
theory underpins the model which captures the
effects of CG on DPs. Governance indicators
(number of independent directors, institutional
investors, board size and managerial shareholding)
and dividend per share of 97 non-financial listed
companies in Nigeria from 1995-2012 drawn from
Analysts’ Data Services & Resources Limited
Ibadan, Nigeria are utilised. The analysis is
conducted at aggregate and sectoral levels. A
representative multi-sector sample is taken from
agriculture (5), automobile (5), building (8), brewery
(6), chemical/paints (9), conglomerates (9),
construction (6), food and beverages, (17),
healthcare (11), industrial/domestic products (10),
petroleum (9) and printing/publishing (3) sub-
sectors. System generalised method of moments
estimation technique is employed in the analysis. It
accommodates firm level characteristics and
addresses autocorrelation bias. The empirical
findings indicate a positive association between
corporate governance and dividend payment,
implying that, previous dividend, number of
independent directors, institutional investors; profits
after tax and gross earnings of firms are the major
drivers of corporate decisions and consequently
dividend payouts in Nigeria during the period under
consideration. Additionally, the analysis underlines
the importance of the mode of operations (sector
classification) in the relationship between corporate
governance practices and dividend payouts in
Nigeria. Based on the results of the study, it is
suggested that more independent directors should be
on the boards of corporate firms and the proportion
of institutional shareholding also be increased to
improve monitoring
Keywords: Corporate governance, Dividend payouts, Agency theory, Institutional
shareholding, Independent directors, Board, Endogeneity.
JEL Classification: G20, G23, G32.
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1. Introduction
In advanced economies, only firms who have relatively grown in size and need more capital for
operations approach capital markets for finance, implying that their ownership would be diffused and
enlarged. To attract more investors, corporate governance standards that could protect the interests of
shareholders need to be enforced (Kowalewski, Stetsyuk and Talavera, 2007). This phenomenon is
relatively new in Nigeria, since firms, formerly owned by colonial allies and administrators were
transferred to some Nigerians as a result of the indigenisation policy of 1970s. Another major economic
transition in the economy in the last three decades (1980’s) is the privatisation (an offshoot of Structural
Adjustment Programme--SAP) of public enterprises. Privatisation is a programme of divestiture of
public enterprises introduced within the framework of macroeconomic reforms. It is one of the
International Monetary Fund’s (IMF) policies to bail her out of economic crisis. It was meant to reduce
absolute reliance of commercially oriented parastatals on the treasury for funding and to encourage
them to approach the stock market for capital. This reform has made ownership of public limited
liability companies in Nigeria, highly concentrated.
In Nigeria, the issue of corporate governance (CG) gained importance in the post-SAP era. This
period witnessed the growth of listed companies. The country witnessed a very high rate of corporate
failures because of the weak corporate culture in these institutions (Anya, 2003). Financial scandals
and scams, poor management and weak internal control systems accounted for some of the lapses in
the operations of some corporate organisations. Moreover, technical mismanagement involving
inadequate policies, lack of standard practices, poor lending, mismatching of assets and liabilities; weak
and ineffective internal control systems as well as poor and lack of strategic planning were prevalent
in the Nigerian corporate industry (Babatunde and Olaniran, 2009; Ebhodaghe, 2014). To regain the
confidence of the public and in response to the need for international CG practices in Nigeria, the
Securities and Exchange Commission (SEC) and Corporate Affairs Commission (CAC) aligned CG in
Nigeria with international CG best practices; spelt out the code of best practices in CG in Nigeria in
2003 for firms that are quoted on the Nigerian Stock Exchange. This was followed by a similar code
by the Central Bank of Nigeria in 2006 (CBN, 2006) and a revised Code of CG (SEC/CAC, 2011) in
Nigeria to address CG lapses in Nigeria.
Emphasis is placed on CG as a result of the high profile of corporate scandals locally and
internationally. Anya (2003) contends that lack of transparency2 obscured the way economic activities
were conducted and consequently, contributed to the alarming proportion of economic/financial crimes
in the financial industry. The financial fraud witnessed in Nigerian corporate sector most especially in
Cadbury Nigeria PLC in 2007 shook investors’ confidence in the Nigerian capital market and the
efficacy of existing CG practices in promoting transparency and accountability3. The fraud was linked
to corruption and fraudulent practices by management of the concerned companies.
In 2001, at the launching of the New Partnership for African Development (NEPAD), African’s
heads of states admitted that the continent missed opportunities to harness financial resources from
domestic and international capital markets for economic growth due to lack of transparency and
accountability (good CG). As a result, CG was included as one of its four thematic areas that member
countries needed to integrate into their national economic programs. Subsequently, African
Development Bank (AfDB) was entrusted with the responsibility to play a leading role in providing
assistance to regional member countries (RMCs) in enforcing CG in them. The objective of the CG,
2 An act of being free from pretence or deceit. 3 An obligation or willingness to accept responsibility.
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according to AfDB (AfDB, 2011) is to promote efficient, effective and sustainable firms that would
enhance societal welfare through wealth creation, employment generation and social development.
Accordingly, the AfDB in collaboration with other Development Partners, aligned its support around
the complementary areas emphasised in the African Union’s NEPAD/Comprehensive African
Agriculture Development Program (CAADP).
In December 2005, AfDB adopted its CG strategy to guide its operations. The CG Strategy is
an important component to the Bank’s larger overall governance policy, as it contributes to building
economic and political governance in African countries by promoting good practices at corporate level.
This was to facilitate the improvement of RMCs CG (AfDB, 2006). The Bank has continued to focus
on improved CG in RMCs’ private sector through technical and financial assistance; projects
implementation and monitoring for continuing improvement in business processes and efficiency to
enhance welfare of stakeholders of corporate firms (AfDB, 2009). Moreover, to enforce NEPAD’s
commitments to CG, the African Peer Review (AFRM) was launched in 2003. It is a mechanism agreed
upon by all African countries to monitor progress of good CG practices. The legal and regulatory
framework of CG for member countries is through each member’s national CG code. Each national
code specifes the firm’s rights and obligations, roles of directors, shareholders and other stakeholders.
In addition, each code specifies disclosure regulations of firms and effective compliance system (ibid).
Dividend is something of value that is distributed to a firm's shareholders on a pro-rata basis
that is, in proportion to the percentage of the firm's shares that they own. A dividend can involve the
distribution of cash, assets, or something else, such as discounts on the firm's products that are available
only to shareholders. When a firm distributes value through dividends, it reduces the value of the
stockholders' claims against the firm. Dividend is not just an outcome of a firm payout policy, rather,
it reflects a combination of investment strategy, financial decision and private information (Miller and
Rock, 1985). Dividend behavior of corporate firms remain a puzzle in financial economics. However,
from traditional finance theories [see Miller and Modigliani (1961), Jensen (1986) and Charitou and
Vafeas (1998)], dividend payouts of firms depend to a large extent on growth prospects, financial
leverage, profitability, corporate tax and firm size.
Good CG is not an indication that large dividend is paid or vice versa. Three scenarios can be
anticipated or conceived in the relationship. First, good CG can indicate good performance but dividend
may be low when there are other pressing needs for earnings such as good investment opportunities
and portfolio-diversification. Hence, a firm that has good CG with good performance may either pay
low dividend or none. Second, dividend may be high in firms with good performance whereas CG is
weak. Lastly, good CG may make firms pay high dividend when corporate performance is high or vice
versa. Dividend payouts (DPs) and CG are two of the most researched areas in financial economics
literature but little is known about the relationship between the two in Nigeria. Indeed, it has been
argued that the findings in developed countries may in fact not be applicable to developing countries
like Nigeria (Aivazian et al, 2003). The foregoing motivates this research which specifically,
investigates how CG influences dividend behaviour of corporate firms in Nigeria. Consequently, it is
hypothesised that CG determines dividend payouts in Nigeria.
The relationship between CG and DPs has been a subject of debate due to divergence of views
in the literature (Bill, Hasan and Song, 2011); while some researchers find negative relationship (Denis
and Osobov, 2008; De Cesari, 2009; Neilsen, 2005) between the two; others report positive association
(Sawickhi, 2009; Byme and O’Connior, 2012; Jiraporn et al, 2011). Notably, there is no consensus in
literature as to the relationship between CG and DPs. The reported conflicting results were due to some
intervening factors (Claessens, Djankov and Klingebiel, 2000). The intervening factors are the
performance indicators such as turnover, gross earnings, profits after tax, investment, growth
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opportunities and leverage which affect revenues of a firm, consequently, influencing dividend
payment (Murekefu and Ouma, 2012; Afsari, 2014; Chin et.al, 2015). Some studies looked only at one
aspect of governance mechanism while others corrected for such shortcoming by using aggregate
governance score which covers several aspects of the governance practices (Adjaoud and Ben-Mar,
2010). The differences in the studies could also be linked to the level of development of the capital
markets of the concerned economies. Further, few studies in financial economics literature have given
due attention to the relationship between CG and DPs but have not taken into account the sector of
operations/industry focus. But the link is important because the association between CG and DPs varies
quite significantly in relation to risk exposure, sectoral diversification factors, operational and financial
activities, all of which could affect dividend payment (Akhtar, 2006). As a result, this study considers
this important variable (sector/industry classification) in addition to previously modified agency model
(Sawicki, 2009) to empirically determine the relationship between CG and DPs in Nigeria as a step
towards bridging the gaps in the literature.
In addition, it contributes to literature in the following ways: First, it employed firm level
measures of governance indicators (four) in contrast to the country level measure employed by Sawicki
(2009); Shao, Kwok and Guedhami (2009); Byme and O’Connor (2012) and O’Connor (2012). Second,
the study employs two estimators for comparison of results; they are differenced generalised method
of moments (DiffGMM) and system generalised method of moments (SYSGMM). After the
comparison, system GMM proved to be the best and most efficient estimator since it uses both level
and lag values as instruments; and corrects endogeneity bias present in our data. Moreover, its empirical
findings show that the relationship between CG and DPs is heterogeneous among subsectors in Nigeria’s
corporate sector; thereby underlying the importance of taking into account sectoral distribution. The rest of the
work is as follows: section 2 gives the theoretical framework and empirical review as section 3 focuses
on methodology and data while section 4 concludes and offers recommendations.
2. Review of Literature
2.1. Theoretical Framework
The agency theory of Jensen and Meckling (1976) is the theoretical foundation of this study. It has been
extensively examined in literature with supported evidence, on the relationship between CG and DPs.
The source of agency problems dated back to the Berle and Means’ (1932) study on the United States
of America’s stock market. Under the agency framework, the relationship between CG and DPs has
two major hypotheses: outcome and substitution. The outcome hypothesis suggests dividend payout is
an outcome of CG, implying that managers in firms associated with weak governance, retain more
cash, making it possible for them to spend more free cash flow for their private benefits at the expense
of their principal (shareholders). Dividend payment is therefore lower in these firms than in those with
strong governance. The hypothesis predicts a positive relationship between DPs and CG. In contrast,
the substitution hypothesis argues that firms with weak governance pay more to substitute for their
weak governance. Investors observed that firms with weak governance might be more prone to
managerial entrenchment. As a result, they demanded large dividends from firms with poor governance
than from firms with strong governance; believing that paying dividend would decrease the free cash
flow, therefore reducing what was left for expropriation by opportunistic managers (Jiraporn, et al,
2011). On the contrary, the substitution model implies an inverse association between DPs and CG.
CG can be used to amend the rules or conditions in which the agent operates so as to restore the
principal's interests for optimal profitability (Investopedia, 2015).
Among various finance theories, the agency theory perspective is the most popular and has
received considerable attentions (Jensen and Meckling, 1976; Fama and Jensen, 1983). It provides the
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basis for governance standards and attempts to solve any conflicts of interests in corporate
firm/company (Maher and Anderson, 1999). In addition, the significance it accords to equity financing
makes it most suitable for the current analysis given the focus on listed firms. One shortcoming of
agency theory is that it ‘relies on an assumption of self-interested agents who seek to maximise personal
economic wealth’ (Bruce et al., 2005). However, this assumption is not pronounced in Nigeria due to
the fact that, prerogative power of dividend declaration lies with the Board of directors.
2.2. Empirical Evidence
CG indicators refer to a set of mechanisms that influence the decisions made by managers when there
is a separation of ownership and control (Larcker, Richardson and Tuna, 2007). Some of the indicators
are: board size, managerial shareholding, institutional shareholding, foreign shareholding, number of
independent directors, leverage, ownership concentration and operations of the market for corporate
control (see, Babatunde and Olaniran, 2009). This paper surveys studies that examined the governance
indicators affecting a firm’s decision to pay or not to pay dividend in a particular year.
2.2.1. Institutional Ownership and Dividend Payouts
Institutional shareholding refers to portfolio of large institutions such as governments, insurance firms,
banks, pension funds, and other nominee firms. (Koh, 2003). Following Short et al (2002);
Karathanassis and Chrysanthopoulou (2005), institutional ownership is defined as the percentage of
shares held by governments, foreign and domestic institutional investors in a firm at a particular point
in time. The presence of institutional investors influences firms’ behaviour basically due to their
substantial shareholdings. Institutional investors, with more available resources and knowledge at their
disposal monitor and influence corporate information which individual investors cannot (Michaely and
Shaw, 1994). Agrawal and Mandelker (1990) point out that institutional investors offer important
monitoring services and operate as a control unit to opportunistic behavior of managers and
consequently. help in reducing agency cost. Eckbo and Verma (1994) show that institutional investors
prefer free cash flow to be distributed in form of dividends.
In a related issue, Shleifer and Vishny (1986) opine that institutional ownership creates the incentives
to monitor management, thereby overcomes the free-rider problem. Claessens and Lang (2000); and
Mitton (2004) show that institutional ownership contributes to financial discipline and ensures that
fewer resources consumed in low return projects and more cash flows are distributed as dividends. In
Wiberg (2008), the relationship between institutional ownership and dividend policy among 189
Swedish companies shows that institutional ownership and dividend payments are positively related.
2.2.2. Managerial Ownership and Dividend Payouts
According to Harada and Nguyen (2009), Short et al (2002), and Karathanassis and Chrysanthopoulou
(2005), managerial ownership refers to the total percentage of equity held by inside shareholders that
take part in the company’s management, either through their natural presence or representation in the
Board of directors or the undertaking of managerial tasks or a combination of the two. Jensen’s (1986)
investigation on UK’s firms maintains that free cash flow theory suggests that managers are reluctant
to pay out dividends, instead retain resources under their control. The evidence shows that dividend
decreases as the voting power of owner-managers increased. Chen et al. (2005) claim a negative
relationship between managerial ownership and dividend policy in Hong Kong. Jensen et al., (1992)
show that insider ownership is associated with lower dividend payout. In addition, some studies suggest
that dividend payment can be regarded as an apparatus to control management as inside ownership
provides direct opportunity to use internal funds on unprofitable projects. This approach anticipates
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negative relationship between insider ownership and dividend payout (Rozeff, 1982; Moh’d, Perry and
Rimbey, 1995; Short, Zhang and Keasey, 2002).
2.2.3. Board Size and Dividend Payouts
The board is considered to be an important part of a firm’s governance mechanism. It is regarded as
the apex court of appeal for resolving various issues, including the agency problem. It acts as a monitor,
and maintains discipline in the firm. It is believed that the decision of the board is supreme (Fama and
Jensen, 1983). Gill and Obradovich (2012) in their investigation on the effect of CG, institutional
ownership and the decision to pay dividends used a statistical sample of 296 U.S. companies listed in
the New York Stock Exchange during 2009-2011. The findings show that there is a positive and
significant relationship between board size and dividend policy. Bokpin (2011) points out that there is
significant and positive relationship between board size and dividend paid. In contrast, Subramaniam
and Susela (2011) empirical analysis of effect of CG on dividend policy of over 300 listed companies
in the Malaysian Stock Exchange supports negative and significant relationship between board size and
dividend policy. The analysis shows that board independence and dividend policy serve as substitutes
in the principal-agency perspective. In the same way, Atmaja’s (2009) confirms that board size has a
significant negative impact on dividend payout of Indonesia listed firms.
2.2.4. Independent Directors and Dividend Payouts
Fama (1980) observes that the board of directors’ competency could be enriched when independent
directors also known as “outside” directors are on the board; as they are regarded as useful device in
reducing agency problem in the firm through monitoring and controlling of executive actions (Bathala
and Rao 1995; Jensen and Meckling 1976). Implying that, independent/non-executive directors serving
on the board help in monitoring and controlling the expropriation behaviour of management and also
assist in appraising the management more objectively (Abidin, Kamal, and Jusoff, 2009). Literature
has emphasised the influence of independent, non-executive directors in relation to DPs (Abdelsalam
et al., 2008; Abor & Fiador, 2013; Adjaoud & Ben-Amar, 2010; Afzal & Sehrish, 2011; Ajanthan,
2013; Mansourinia et al., 2013). Abor and Fiador’s (2013) investigation on the relationship between
CG mechanisms and firms’ DP ratio from sub-Saharan Africa for the period 1997 to 2006; shows that
independent directors influence the dividend payment of Kenya and Ghana significantly . The results
indicate that the “outside” members on the board have a tendency to safeguard the shareholders’
interests through higher payments of dividend. In the same vein, Afzal and Sehrish (2011) reveal that
proportion of “outside” directors has a positive and significant correlation with the DPs of the firms.
Adjaoud and Ben-Amar (2010); Schellenger et al (1989); Uwuigbe et al (2015); also further support
the significant and positive influence on DPs. However, the study of Ajanthan (2012) supports an
insignificant association between board independence and DPs in his study of hotels and restaurant
firms in Sri Lanka. In addition, an insignificant and negative relationship exists between independent
directors and their firm’s willingness to pay dividend (Jones, 2002; Mansourinia et al. 2013;
Abdelsalam et al. 2008; Abor and Fiador, 2013; Cotter and Silvester, 2003; Borokhovich et al. 2005;
Nwindobe, 2016).
The review of the literature above lays a solid basis in identifying research gaps. In general, the
consensus is that CG enhances DPs but the magnitude of impact differs. Some of the reviewed papers
have some methodological shortcomings: the use of a simple correlation analysis in Schellenger et al.
(1989), Chi-square in Nwindobe, 2016; small sample size in Uwuigbe et al, 2015; and the use of event
study in Borokhovich et al. (2005). More importantly, a sizeable number of past studies employed
ordinary least square regression (Sawicki, 2005; Shao, Kwok and Guedhami, 2009; Cotter and Silvester
2003; Kowalewski et al., 2007; Bebczuk, 2005; John and Knyazeva, 2006; Klein, 2002); which could
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not address endogeneity bias. Moreover, it is also noted that most of the papers were conducted on
industrial and emerging economies. The differences in the studies could be linked to the level of
development of the capital markets of the concerned economies. Differences in the legal environments
is another factor. For instance, the legal environments in the United States and United Kingdom support
high overall standards of investors’ protection, so firms with better governance tend to avoid the costs
associated with dividends in an attempt to achieve a more efficient investment policy (John and
Knyazeva, 2006). La Porta et al. (2000) posit that firms in countries with strong legal systems for
minority corporate outsiders pay higher dividends in comparison with countries where legal systems
are weak. Another controversy on the degree of association between CG and DPs may be due to the
differences in firm- specific characteristics and country- specific characteristics. The existing gap in
knowledge which this study fills is the explanation of the role of CG on dividend behaviours of 97 non-
financial firms in 12 subsectors listed on Nigerian Stock Exchange.
3. Methodology and Data Our model is formulated in the spirit of Sawicki (2009) post-Asian crisis modified agency model which
extends the agency cost of equity version in the investigation conducted at country-level in which five
countries were represented. The choice of adapting Sawicki (2009) model is driven by it, being set in
panel framework. According to Baltagi (2008), panel data analysis provides a better understanding of
most economic phenomena, which in most cases are dynamic in nature. Therefore, dynamic unbalanced
panel, is the best suited and therefore, adopted method in the analysis. This is done by employing panel
estimation and including the lag of the dependent variable as one of the independent variables.
In the econometric literature, such a model is referred to as a dynamic panel model. A general way of
specifying such a model is as follows:
𝒀𝒊𝒕 = ∑ 𝒚𝒊,𝒕′𝒎
𝒋=𝟏 − 𝒚𝒋−𝟏 + 𝒙𝒊,𝒕′ 𝜷 + 𝜶𝒊 + 𝝀𝒕 + 𝜺𝒊,𝒕 i= 1, 2… N (1)
𝜆𝑡 and β are parameters to be estimated. Xit is (KxL) vector of strictly exogenous covariates, αi and λt
are the unobservable individual and the time effects respectively and εit Ϟ iid (0, ϛ). The standard panel
models such as fixed and random effects models are biased and inconsistent, as the lagged dependent
variable is correlated with the error term εit. The inconsistency of the estimated parameters persists
even if no correlation in the error term is assumed (Windmeijer, 2005). The general approach to
estimate a dynamic panel model relies on Arellano and Bond, (1991); Arellano, and Bover, (1995)
which suggest a Generalised Method of Moments (GMM) Xtabond2 estimator using the instrumental
variables technique. There are two approaches to GMM: Difference GMM and system GMM.
Although, Diff-GMM and System-GMM estimators are suited for 'small T and large N’ but they make
use of extra moment conditions. Also, they are robust to heteroscedasticiy and distributional
assumptions. GMM framework accommodates unbalanced panels and multiple endogenous variables.
In addition, each uses both level and lag values as instruments; and corrects endogeneity bias in panel
data that ordinary least squared cannot address.
Nevertheless, Difference GMM (Diff GMM) suffers from weak instrumentation but system
GMM (SYSGMM) augments it by estimating simultaneously in differences and levels (Roodman,
2008). SYSGMM originated in Arellano and Bover (1995) but Blundell and Bond (1998) articulated
the condition in which the novel instruments associated with it are considered valid (ibid). Arellano
and Bond (1991) and Arellano and Bover, (1995) also submit that even more effective estimators can
be estimated using additional lags of the dependent variable as instruments; however, employing more
lags as instruments may lead to over-identification of the model. In addition, SYSGMM provides
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consistent estimators if the underlying assumption of no second order autocorrelation in the residuals
is fulfilled. Arellano and Bover (1995) however, suggest a specification test (Sargan) to check for the
over-identification and AR (2) test for second order autocorrelation in the model.
Studies have shown that dividend can be explained by some firm specific factors such as cash
flow related problem (Jensen and Meckling, 1976; Jensen, 1986); profitability (Barlett and Ghoshal,
1989; Fama and French, 2001); market capitalisation (Fama and French, 2001); gross earnings (De
Angelo et al, 2004; Bulan et al, 2007); and turnover (Odedokun, 1995). Given that CG is not the sole
factor affecting DPs; two control variables: gross earnings and profit after tax are introduced to isolate
other contrasting incentives that have been found to influence DPs.
3.1. Model Specification
For empirical estimation4, dynamic panel data models as expressed in (2) and (3) are specified.
Divit = β1Divit-1+β2(BSit)+β3(INSTit) +β4(INDDIRit) – β5(MANSit) + β6(logPATit)+
β7(logGENit)+τt+ψi+εit (2)
Divit = β1Divit-1+β2(BSit)+β3(INSTit) +β4(INDDIRit) – β5(MANSit) + β6(logPATit)+
β7(logGENit)+SEC1it… SECnit +τt+ψi+εit (3)
β1>0, β2>0, β3>0, β4>0, β5<0. Β6>0, β7>0
Where:
Divit is the dividend paid of firm i at time t
Divit-1 is the lagged value of the dividend paid of firm i at time t
(BSit) is the board size of firm i at time t
(INSTTit) represents the stake of institutional investors of firm i at time t.
(MANSit) is the shareholding of directors of firm i at time t.
(INDDIRit) refers to number of independent directors of firm i at time t.
(PATit) is the profit after tax of firm i at time t.
(GENit) refers to the gross earnings of firm i at time t.
SEC1it represents sector 1
SECnit depicts sector n
τt represents time effects.
ψi is the firm specific fixed effects.
β1 … β7 are coefficients of the parameters.
εit represent the stochastic term.
3.3. Scope and Source of Data
This study uses internal governance indicators: institutional ownership, board size, managerial
shareholding and number of independent directors as proxies for CG. The choice is justified on the
grounds that they are more flexible in principle and can be varied as circumstances dictate. Profits after
tax (PAT) and gross earnings are controlled for. 97 non-financial firms in 12 subsectors listed on the
Nigerian Stock Exchange are the dataset, covering a time span of 1995 to 2012; the choice of period
and subsectors is informed by availability of data. The 12 subsectors of the non-financial corporate
firms covered in the study are: agriculture, (5); automobile and tyres, (5); building materials, (8);
4 Data management and analysis were performed using STATA 14.
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brewery, (6); chemical and paints, (9); conglomerates, (9); construction, (6); food and beverages, (17);
healthcare, (11); industrial and domestic products, (10); petroleum and marketing, (9) and printing and
publishing, (3). Data are mainly sourced from Analysts’ Data Services & Resources Limited, Ibadan,
Nigeria and the sector selection is defined by the data.
Table 1: Operational Definitions of Key Variables
Variables Name Definition Measurement
Dependent
variable
Dividend payout DIV It is the return on equity payable to shareholders. It
is also referred to as dividend per share.
Kobo
Independent
variables
Board size BS Total number of directors on the Board of
directors.
Nominal
value
Institutional
Shareholding
INST The total percentage of shares owned by
governments, foreigners and companies.
%
Managerial
Shareholding
MANS Proportion of directors’ shareholding to total
shares in the paid-up share capital.
%
Independent
Directors
INDDIR Number of independent directors on the Board of
directors. It is the number of directors without
shareholding in the firms. It is also called outsiders
on the Board.
%
Controlled
variables
Profits after tax PAT It is calculated as profits before tax, less tax and
other expenses. It is expressed in its logarithm form.
Naira
Gross Earnings GEN Total Turnover. It is expressed in its logarithm
form.
Naira
Source: Author
3.4. Findings
3.4.1. Descriptive Analysis
Table 2 shows the details of descriptive statistics of variables that affect dividend payments of the 97
selected firms, quoted on the Nigerian Stock Exchange between 1995 and 2012. The table shows that
DPs ranges from ₦0 to ₦10 with a mean of ₦0.45 and standard deviation of ₦1.20. The institutional
shareholding (INST) ranges from 0% to 100 percent with a mean and standard deviation of 45.44
percent and 26.23 percent respectively. Managers’ shareholding (MANS) ranges from 0% to 46.8
percent with a mean of 2.15% and a standard deviation of 26.23 percent. The mean number of
independent directors (INDDIR) is 41 percent; implying that for the sampled firms, some of the Board
members are relatively less independent with 41 percent being non-executive directors. The profits
after tax (PAT) reports a minimum value of ₦0 billion, while the maximum value is ₦10.3 billion. On
the other hand, the variation in gross earnings is between ₦5.44 and ₦11.8 billion. The mean Board
size (BS) is nine, with a maximum of twenty-one directors, this suggests that Nigerian quoted
companies have board size considered ideal (SEC/CAC, 2011). Institutional shareholding records the
highest mean value (45.44 percent) amongst other governance indicators.
13
Table 2: Descriptive statistics of variables
ALL
FIRMS
DIV
BS
INST
INDDIR
MANS
PAT
GEN
N 1,235 1,102 1,235 1,073 1,141 1,068 1,217
Min 0 3 0 0.33 0 0 5.44
Max 10.00 21 100 0.92 46.8 11.1 11.83
Mean 0.45 9 45.44 0.41 2.15 10.3 9.4
Std.
Deviatn
1.20 2.63 26.23 0.24 26.23 0.32 0.91
Source: Computed by Author
3.4.2. Correlation Analysis
Table 3 below summarises the results of preliminary pairwise correlation among the variables, as well
as their associated levels of statistical significance. It serves two important purposes. First, it determines
whether there is a bivariate relationship between each pair of the dependent and independent variables.
Second, it ensures that the correlations among the explanatory variables are not so high to the extent of
posing multi-collinearity problems. The results show that there is a positive correlation between
dividend payout and other variables. Also, the correlation within the explanatory variables is low,
suggesting that there is no problem of multi-collinearity. As expected, dividend is positively,
statistically and significantly correlated with all the regressors except managerial shareholding.
Generally, amongst the four corporate governance indicators, board size, institutional shareholding and
board independence have positive and significant impact on dividend payment, this is very unlikely for
managerial ownership.
Table 3: Correlation Matrix of the Variables
DIV BS INST INDDIR MANS GEN_L PAT_L
DIV 1
BS 0.19***
(0.0000)
1
INST 0.09**
(0.0024)
0.06*
(0.0737)
1
INDDIR 0.15***
(0.0000)
0.22***
(0.0000)
0.39***
(0.0000)
1
MANS -0.03
(0.3453)
-0.03
(0.2680)
0.05*
(0.0833)
-0.03
(0.2899)
1
GEN_L 0.38***
(0.0000)
0.38***
(0.0000)
0.23***
(0.0000)
0.28***
(0.0000)
-0.01
(0.6314)
1
PAT_L 0.08*
(0.0141)
-0.02*
(0.0483)
0.05
(0.1327)
0.04
(0.2839)
-0.002
(0.9602)
0.06*
(0.0752)
1
NOTE:*, ** and *** depict 10%, 5% and 1% levels of significance respectively. Significance levels are in parenthesis
Source: Computed by Author
14
3.4.3. Sectoral Representation
Table 4 depicts the representation of the sampled firms among listed subsectors on the floor of Nigerian
stock exchange as at February, 2014. The dataset is made up of 81.5 percent non-financial firms of the
corporate sector, therefore, our dataset is highly representative.
Table 4: Sample Breakdown
S/N Subsector Frequency Percentage Selected
1 Agriculture 6 83.3
2 Automobile & Tyres 5 100
3 Brewery 7 85.7
4 Building 10 80
5 Chemical 10 90
6 Conglomerates 9 100
7 Construction 10 60
8 Food & Beverages 18 88.8
9 Healthcare 12 91.7
10 Industrial/Domestic 14 71.4
11 Petroleum/Marketing 14 64.3
12 Printing 4 75
Total Firms 119 100
Total Sampled 97 81.5% Source: Computed by Author
3.4.4. Relationship between Corporate Governance and Dividend Payouts
To examine the impact of corporate governance on dividend payouts in Nigeria, two estimators are
employed: difference generalised method of moments (Diff GMM) and system generalised method of
moments (SYSGMM). The rationale is based on the fact that pooled OLS estimator does not control
for the joint endogeneity of explanatory variables or for the presence of firm-specific effect. In addition,
fixed effect and random effect estimators respectively eliminate firm-specific effect but do not account
for joint endogeneity of explanatory variables. It has been established that OLS and static panel could
not address endogeneity bias that might surface in any dataset (John and Knyazeva, 2006; John and
Kadyrzhanova, 2008). Table 4 presents the dynamic panel (difference GMM & system GMM) results.
The Wald/F statistics value of DIFF GMM shows that all explanatory variables are statistically
significant at 1% in explaining changes in dividends payout; meaning that the model is well specified
and that CG influences DPs. Specifically, there is a positive and significant relationship between
previous DP and current level of DP. According to the difference GMM results, current DP increases
by 21.4 percent given a 1% increase in previous DP. The percentage of institutional investors impacted
on DP. DP increases by 0.6% given a 1% increase in the shareholding of institutional investors.
However, the DIFFGMM estimator accounts for joint endogeneity and firm-specific effects but
eliminates valuable information and used weak instruments. The number of instruments used in
SYSGMM is higher than that of DIFFGMM, this raises concerns about its usability.
15
System GMM (Xtabond2) is the last resort method of analysis in this study, because ‘it uses
more instruments and does not impose any restriction on the distribution of the data, which are
characterised by heavy-tailed and skewed distributions’ (Chauss´e, 2010). It depends only on moment
conditions, it is a reliable estimation procedure for many models in economics and finance. In addition,
it overcomes all the weaknesses of the other above named estimators and it is more efficient than
Xtabond1. The empirical results of the System GMM show that most of the CG indicators are
statistically significant (with the correct sign) in explaining changes in DPs; unexpectedly managerial
shareholding though positively related but not significant. Previous dividend payout is positive and
significantly related to DP. Current DP increases by 45 percent given a 1% increase in previous
dividend. The percentage of institutional investors is also positively related to DP. This relationship is
statistically significant at 1%, implying that a 1% increase in the percentage of institutional investors
increases DP by 0.09%. Board size has a positive and significant relation with dividend, indicating that
when board size increases, the propensity to pay higher dividend increases. The possible explanation
of this is that a large board size gives room for greater specialisation which enhances effective
monitoring (Abor and Fiador, 2013).
Also, the results show a significant relationship between number of independent directors and
dividend payout, implying that given a 1% increase in the percentage of independent directors, dividend
payout increases by 78 percent. Independent directors are non-executive members of the Board, they
serve as a monitoring tool in reducing managers’ expropriation. Profit after tax (PAT) and gross
earnings have substantial and significant association with dividend payout respectively. The system
GMM estimator gives more precise estimates and most importantly corrects for the endogeneity
problem associated with the relationship between DPs and CG. A further diagnostic, Sargan (1958) test
indicates that the instruments used to check the endogeneity problem are valid and strictly orthogonal
with the regression disturbance term (see table 5). Therefore, the lags of the dependent variable and
other variables used as instruments are strictly exogenous, thus good instruments and justified the
validity of the model. In addition, AR (2) for autocorrelation test shows the presence of no second order
serial correlation problem.
The controlled variables also have some explanatory effects on dividend. The coefficients of
profit after tax and gross earnings are positive and significant, ceteris paribus; indicating that profitable
firms have more cash to distribute to shareholders. Consistent with the literature, a positive and
significant association exists between dividend payment, profit after tax and gross earnings (controlled
variables) respectively. These variables suggest that there is a high probability that profitable firms pay
out larger dividends (Jiraporn, et al, (2011); Al-Malkawi, (2007); Atmaja, (2009); Denis and Osobov,
(2009); Kumar, (2004). It is evident in the results that lagged (previous) dividend payout, board size,
number of independent directors, institutional investors, profits after tax and gross earnings respectively
play vital role in determining the current year dividend payout in the sampled firms. Our result of a
positive but insignificant relationship between managers’ shareholding and dividend payout did not
support the hypothesis that managers expropriated shareholders’ wealth. This conforms to the reality
in Nigeria, where the Board has the prerogative power to declare dividend. Nevertheless, it contradicts
Jensen (1986); Eckbo and Verma (1994); Short et al (2002); Chen, Chen and Wei (2003); and Farinha
(2003); which conclude that managers were reluctant to pay out dividends but preferred to retain cash
flow for their perquisites.
The empirical results of this study indicate that a significant positive relationship exists between
CG and DPs of Nigerian corporate firms. These findings are consistent with La Porta et al (2000); Allen
et al (2000); Farinha (2003); Mitton (2004); Byme and O’Connior (2012); Pan (2007); Jiraporn et al
(2011); Sawicki (2009) and Mehrani et al (2011). In contrast, the results do not support Officer (2007);
16
Neilsen (2005); John and Knyazeva (2006); De cesari (2009) and Denis and Osobov (2008). The
variation may be as a result of superior estimation technique (SYS GMM-Xtabond2) that this paper
employs, it addresses endogeneity problem in the data (previous studies neglected it). In addition, most
of the past studies are based on advanced and emerging economies and not developing countries like
Nigeria. Previous studies on Nigeria used elementary technique such as Chi-square (Nwindobie 2016);
and small sample size (Uwuigbe et al, 2015).
Table 5: Relationship between Corporate Governance and Dividend Payouts of Sampled Firms
Variables Difference GMM System GMM
DVDP(-1) 0.2141***
(4.54)
0.4521***
(13.22)
BS -0.0187
(-0.86)
-0.0298*
(-1.40)
INST 0.0055*
(1.89)
0.0085***
(2.79)
MANS 0.0001
(0.01)
0.0006
(0.07)
INDDIR 0.2905
(0.26)
0.7830***
(2.94)
PAT_L 3.7424***
(4.04)
2.2522***
(2.67)
GEN_L 0.0012
(0.01)
0.6505***
(5.27)
Constant -38.4625***
(-4.15)
-29.6323***
(-3.51)
NO Of OBS 821 821
No. Of Instruments 142 158
F Statistic (Wald chi2)
49.27***
(0.0000)
407.81***
(0.0000)
AR(1) test -2.409*
(0.0160)
-2.848**
(0.0044)
AR(2) test -0.5942
(0.5524)
-0.0277
(0.9777)
Sargan Test 456.13***
(0.9876)
495.39***
(1.0000) NOTE: Two-step GMM results are reported
*, ** and *** depict 10%, 5% and 1% levels of significance respectively. Z Stat are in parentheses
Source: Computed by Author
17
3.4.5. Sectoral Analysis
The sectoral effects are captured in Tables 6a-6d. They show that past dividend exerts significant and
positive influence on current dividend per share of most of the subsectors, this is in support of Lintner
(1956). In Agriculture, chemical/ paints, conglomerates, and healthcare subsectors, none of the
governance variables significantly influenced dividend payouts respectively. Oil discovery has made
agriculture subsector to be secondary to the oil sector in Nigeria’s economic growth. Only risk takers
who are indifferent to dividend payment invest in it. Institutional investors, and board independence
positively and significantly determine shareholders’ returns of automobile & tyres subsector. The
results show that board independence at 5% significantly influence the shareholders’ returns.
Institutional shareholding and board independence significantly drive dividend payouts in construction
and food & beverages respectively while board size and institutional investors impact
petroleum/marketing and printing/publishing subsectors respectively. The implication is that, when
board size, board independence and percentage of institutional investors increase respectively; they
influence these sub-sectors to pay dividend. However, an increase in directors’ shareholding lead to a
decrease in dividend per share. Managerial shareholding positively influence dividend in that sector.
The negative relationship of directors’ shareholding with dividend payouts in agriculture,
chemical/paints, conglomerates, construction, food & beverages, industrial/domestic,
petroleum/marketing and publishing/printing sub-sectors implies that the shareholders of the firms in
these sub-sectors are not protected against expropriation of their management. Consequently, their
firms’ values and shareholders’ wealth could be at stake.
Based on the empirical findings, the diagnostic F statistic of the model reveals that it
successfully relates the explanatory variables to the dependent variable (dividend payout). Also, the
Sargan diagnostic test indicates that the instruments used to check the endogeneity problem are valid
and strictly orthogonal with the regression disturbance term. In addition, the AR (2) autocorrelation
test indicates no second order serial correlation problem and therefore, the lags of the dependent
variable and other variables used as instruments are strictly exogenous, thus good instruments.
Summarily, the reported results infer that the link between CG and DPs differs by sector of operations.
This may be due to risk exposure, sectoral diversification factors, operational and financial activities
all of which could affect dividend payment. These findings are consistent with evidence that suggest
that there is significant variation in dividend payout among industries [Baker, (1988); Michel, (1979);
Baker, Farrelly and Edelman, (1985); Horace, (2002); Kapoor (2009); Alzomaa and Al-Khadhiri
(2013)
18
Table 6a: Analysis of Sectoral Dimension of the Relationship between Corporate Governance and Dividend Payouts of the
Sampled Subsectors (Agriculture, Automobile & Tyres, Breweries)
AGRICULTURE AUTOMOBILE & TYRES BREWERIES
Diff GMM System GMM Diff GMM System GMM Diff GMM System GMM DIV (-1) 5.436
(0.74)
0.527
(1.07)
0.38**
(2.03)
0.505***
(3.02)
2.426
(0.97)
0.574***
(2.79)
BS -0.334
(-1.20)
-0.472
(-1.07)
-0.0001
(-0.03)
-0.0001
(-1.05)
-0.06
(-0.37)
0.114
(0.53)
INST -0.019
(-0.29)
0.254
(1.02)
-0.001
(-0.40)
0.001
(0.68)
0.022
(0.89)
0.003
(0.57)
MANS -0.095
(-1.38)
-0.053
(-0.75)
-0.57
(-0.03)
0.392
(1.07)
2.01
(0.63)
1.451
(0.96)
INDDIR -0.58
(-1.12)
6.736
(1.26)
0.017
(0.013)
0.217***
(2.68)
18.659**
(2.69)
4.61***
(3.51)
PAT_L 6.274
(1.38)
7.782
(1.04)
0.011**
(2.13)
0.011*
(1.68)
1.12
(1.41)
2.801**
(2.24)
GEN_L -6.412
(-1.41)
-9.933
(-1.05)
0.06*
(1.65)
0.092**
(2.09)
1.13
(0.98)
3.112
(0.78)
_cons -37.571
(-1.03)
9.103
(1.05)
-46.65*
(-1.68)
-55.415*
(1.66)
151.05**
(2.46)
-38.412*
(-1.89)
NUMOF
OBS
21 38 34 42 36 48
F-
STATISTICS
99.18
(0.0000)
435.21
(0.0000)
101.53
(0.0000)
43.59
(0.0000)
2482.95
(0.0000)
1514.86
(0000)
AR1 -4.20
(0.000)
-5.30
(0.0001)
-1.11
(0.0001)
-2.90
(0.0002)
-2.08
(0.0000)
-1.46
(0.0001)
AR2 -2.83
(0.4070)
-0.73
(0.5601)
-1.04
(1.0000)
-1.89
(0.9270)
-2.44
(0.8120)
-1.12
(1.0000)
SARGAN
TEST
15.9814
(0.3145)
16.38238
(0.9035)
35.7164
(0.1462)
40.12371
(0.4193)
36.25452
(0.6334)
38.1648
(0.2689) NOTE: Two-step GMM results are reported
*, ** and *** depict 10%, 5% and 1% levels of significance respectively. Z Stat are in parentheses
Source: Computed by Author
19
Table 6b: Analysis of Sectoral Dimension of the Relationship between Corporate Governance and Dividend Payouts of the
Sampled Subsectors (Building Materials, Chemical & Paints and Conglomerates)
BUILDING MATERIALS CHEMICAL & PAINTS CONGLOMERATES
Diff GMM System GMM Diff GMM System GMM Diff GMM System GMM
DVDP (-1) -2.247
(-0.61)
-5.004
(-1.04)
-0.425
(-0.37)
0.25**
(2.62)
-8.0
(-1.04)
2.625**
(2.14)
BS -0.193
(-0.45)
-0.014
(-0.09)
0.005
(0.83)
-0.01
(-0.26)
2.823
(0.76)
0.795
(1.39)
INST 0.008
(1.70)
-0.001
(-0.04)
-0.005
(-1.02)
0.006
(3.06)
0.045
(1.18)
0.039
(1.31)
MANS 0.794**
(2.63)
1.511*
(1.70)
0.005
(0.46)
-0.002
(-0.27)
-25.764
(-0.76)
-0.569
(-1.05)
INDDIR 14.80**
(2.66)
8.511**
(2.86)
0.46*
(1.67)
0.095*
(0.17)
0.308**
(2.16)
18.28**
(2.38)
PAT_L 13.909*
(1.71)
9.136*
(1.89)
0.308
(1.02)
0.275
(1.21)
4.01
(2.05)
16.816*
(2.15)
GEN_L 0.213*
(1.81)
-0.597
(-0.48)
0.41
(1.06)
0.326
(1.18)
2.979
(0.84)
0.136
(0.14)
_cons -151.22
(-0.76)
-92.05
(-1.01)
-306.62
(-0.62)
-513.00
(-0.71)
-19.581
(-0.10)
171.985
(0.76)
NUM OF
OBS
35 59 66 89 57 83
F-
STATISTIC
9902.86
(0.0000)
23.61
(0.0013)
24264.4
(0.0000)
1809.1
(0.000)
929.53
(0.0000)
326.00
(0.0000)
AR(1) 3.26
(0.0001)
0.01372
(0.0891)
0.1002
(0.0712)
-2.1043
(0.003)
-3.0173
(0.0000)
-3.0401
(0.0001)
AR(2) -2.07
(1.000)
-0.7008
(0.4834)
0.1156
(0.7842)
-0.2814
(1.000)
-0.5729
(0.8424)
-0.3818
(0.7026)
SARGAN
TEST
2.740
(1.0000)
2.01
(1.0000)
48.2458
(0.1802)
47.475
(0.175)
40.641
(1.0000)
0.05967
(1.000) NOTE: Two-step GMM results are reported
*, ** and *** depict 10%, 5% and 1% levels of significance respectively. Z Stat are in parentheses
Source: Computed by Author
20
Table 6c: Analysis of Sectoral Dimension of the Relationship between Corporate Governance and Dividend Payouts of the
Sampled Subsectors (Construction, Food & Beverage and HealthCare)
CONSTRUCTION FOOD & BEVERAGE HEALTHCARE
Diff GMM System GMM Diff GMM System GMM Diff GMM System GMM
DIV (-1) -2.309
(-1.13)
0.603**
(2.15)
0.039
(0.24)
0.195**
(2.55)
0.212
(0.22)
0.098***
(2.89)
BS 0.194*
(1.69)
0.205
(1.62)
-0.005
(-0.59)
-0.008
(-0.30)
0.035
(0.73)
0.011
(1.05)
INST -0.014
(-1.50)
-0.015
(-1.56)
0.0002
(0.50)
0.002
(0-61)
0.002
(0.43)
-0.0
(-0.42)
MANS 0.00009
(0.03)
0.0003
(0.18)
-0.026
(-0.25)
0.05
(0.89)
0.033
(0.64)
-0.041
(-1.00)
INDDIR -0.675
(-1.05)
-0.091
(-0.72)
-0.254
(-2.05)
-0.166
(-0.36)
0.032
(0.13)
-0.200
(-1.10)
PAT_L 0.028
(0.83)
0.593**
(3.06)
-0.821
(-0.88)
0.204
(0.26)
0.705*
(1.71)
0.013**
(2.14)
GEN_L 0.531
(0.75)
0.630**
(3.01)
0.032
(0.56)
0.177**
(2.85)
0.837
(0.67)
0.318
(0.99)
_cons -84.05*
(-0.99)
-85.089
(-0.87)
8.549
(0.90)
0.663
(0.07)
-335.21
(-0.38)
-178.288
(-1.25)
NUM OF
OBS
43 56 90 120 42 62
F-
STATISTIC
113.05
(0.0000)
258.39
(0.0000)
3845.64
(0.0000)
25081.2
(0.0000)
124.05
(0.0000)
523224.7
(0.0000)
AR(1) -0.2677
(0.0557)
-2.6599
(0.0125)
-0.4876
(0.0723)
-1.1679
(0.0428)
-2.2768
(0.007)
-1.26797
(0.0512)
AR(2) 0.3973
(0.6674)
-0.2468
(0.8509)
0.2337
(0.6876)
-1.067
(0.2860)
-2.0761
(0.8206)
-1.0761
(0.4806)
SARGAN
TEST
14.8914
(0.6154)
31.8254
(0.6335)
4.88438
(1.0000)
7.13619
(1.0000)
31.7032
(0.4219)
14.8334
(0.9013)
NOTE: Two-step GMM results are reported
*, ** and *** depict 10%, 5% and 1% levels of significance respectively. Z Stat are in parentheses
Source: Computed by Author
21
Table 6d: Analysis of Sectoral Dimension of the Relationship between Corporate Governance and Dividend Payouts of the
Sampled Subsectors (Industrial/Domestic, Petroleum/Marketing and Printing/Publishing)
INDUSTRIAL/DOMESTIC PETROLEUM/MARKETING PRINTING/PUBLISHING
Diff GMM System GMM Diff GMM System GMM Diff GMM System GMM
DIV (-1) 0.448**
(3.05)
0.62***
(3.28)
-0.220
(-0.38)
0.270**
(4.05)
0.22
(1.12)
0.215**
(1.89)
BS -0.020
(-1.64)
-0.103
(-0.63)
-0.012
(-0.03)
-0.069
(-2.5)
0.151
(1.08)
0.168
(0.96)
INST -0.001
(-0.84)
-0.001
(-0.40)
0.008
(0.22)
0.010
(0.27)
0.025**
(2.95)
0.024**
(3.28)
MANS -0.002
(-0.52)
0.006
(0.37)
-1.785
(-0.25)
-0.675
(-0.08)
-0.218
(-1.01)
-0.262
(-0.88)
INDDIR 0.215
(0.87)
1.467
(0.67)
1.081
(0.08)
2.639
(-0.22)
-4.373
(0.94)
-4.400
(-1-56)
PAT_L 0.177
(0.96)
0.099
(1.26)
15.240
(0.18)
15.313
(0.17)
22.11**
(2.73)
0.099**
(2.57)
GEN_L -0.170
(-0.85)
0.135
(1.42)
4.424
(0.27)
4.874
(0.73)
0.101
(0.60)
-0.003
(-1.34)
_cons -32.228
(-1.01)
-35.114
(1.29)
111.864
(0.13)
212.311
(0.24)
-77.324
(-0.84)
-145.28
(-0.78)
NUM OF
OBS
76 96 64 84 41 47
F-
STATISTIC
22841.18
(0.0000)
35619.9
(0.0000)
2.53
(0.9249)
19.19
(0.0076)
20.76
(0.0004)
1436.45
(0.0000)
AR(1) -2.3877
(0.0074)
-2.2687
(0.0044)
-3.1769
(0.0003)
-2.2867
(0.0004)
-3.2410
(0.0065)
-2.0223
(0.0008)
AR(2) 0.1397
(0.6476)
0.1973
(0.4876)
-0.7546
(0.2608)
0.19337
(0.8467)
0.3818
(0.6063)
-0.6080
(0.8434)
SARGAN
TEST
37.04
(1.0000)
47.9647
(0.6614)
35.37987
(1.0000)
22.6317
(1.0000)
33.5786
(1.0000)
12.3843
(0.9130)
NOTE: Two-step GMM results are reported
*, ** and *** depict 10%, 5% and 1% levels of significance respectively. Z Stat are in parentheses
Source: Computed by Author
22
4. Conclusion and Recommendations
This study contributes to the ongoing debate on the role of corporate governance on dividend
payouts of corporate firms. It is carried out to examine the impact of CG on DPs of 97 non-financial
quoted firms in Nigeria between 1995 and 2012. The specific objectives of this study are two folds,
first, to investigate the impact of CG on DPs at macro level. Second, to examine the effect of CG
on dividend policies at sectoral level. The modified agency model of Sawicki (2009) is adapted
with the dynamic panel model as the estimation technique. The four indicators capturing CG are
board size, institutional shareholding, number of independent directors and directors’ shareholding
while profits after tax and gross earnings are the remaining regressors.
The findings indicate a positive and significant relationship between board size and DPs,
implying that when board is relatively large; its members use their power to influence DPs. The
relationship between institutional shareholding and DPs is positive and significant implying that
powerful institutional investors exert influence on dividend payouts. Additionally, a positive
association between the number of independent directors and DPs is predicated as larger boards
with more independent directors influence dividend payments. In contrast, the findings indicate
that managers’ shareholding is not significantly associated with DPs; it may be due to its small
shareholding, therefore, expropriation of cash flow for managers’ perquisites is limited. These
results are in support of the outcome hypothesis (Jiraporn, et al., 2011; Adjaoud & Ben-Amar,
2010, Ajanthan, 2013), assuming that governance practice influences DPs. This means that,
previous dividend, number of independent directors, institutional investors, profits after tax and
gross earnings of firms are the major drivers of corporate decisions and consequently, DPs in
Nigeria during the period under consideration.
Moreover, it is discovered that there are variations in the link between CG and DPs among
the subsectors. The relationship is positive in only automobile/tyres, building/materials,
conglomerate, construction, and printing/publishing respectively while it is negative in agriculture,
brewery, chemical/paints, food and beverages, healthcare, industrial/domestic products, and
petroleum sub-sectors respectively. This may be due to risk exposure, sectoral diversification
factors, operational and financial activities all of which could affect dividend payment. However,
it may imply that the shareholders of the firms in these sub-sectors are not protected against
expropriation of their management. Consequently, their firms’ values and shareholders’ wealth
could be at stake. The non-significance of governance indicators in these subsectors might be due
to the lower stake of their board members. Also, the number of independent directors, who are
specialists in various areas in these subsectors is relatively small. This might have ruled out applied
innovation that would have enhanced productivity and performance of these subsectors for higher
profitability which could have impacted DPs. Agriculture for instance, has been neglected for some
decades. The prevalent environmental factors in the petroleum subsectors (conflicts in the Niger
Delta region for example) also might have been another reason.
The results are robust as they attenuate endogeneity bias via system GMM (Xtabond2) as
against static OLS estimators used in previous studies. Nevertheless, the study does not support
the agency theory assumption of principal-agent conflicts. This is as a result of the high
concentration of shareholding which is the feature of the Nigerian corporate sector, where
managers/agents have little room to exercise corporate discretions. This work extends the frontier
of research knowledge as it extends the theoretical prediction of the agency theory and
23
disaggregates the relationship between CG and DPs into sectors of operations in the modified
Sawicki (2009) model. The empirical results demonstrate that the sectoral mode of operations
matters in the relationship between CG practices and DPs in Nigeria.
Based on the results of the study, the following are recommended:
First, considering gross earnings and profit after tax, the results show that they significantly
influence DPs. Nigerian government therefore, needs to make business environment more enabling
in ensuring that costs of doing business in Nigeria reduce to the barest minimum so that existing
companies can be motivated to continue in business and new ones can also come on board.
Enabling environment would lead to good performance, consequently, higher profit before tax
which tends to be a juicy avenue for the government to generate more revenue in the form of
corporate/companies’ tax. In addition, firms’ good performance will positively affect DPs,
withholding taxes from dividend payments to the shareholders would increase accrued revenue to
the government for further investment in the economy.
Second, boards of directors of agriculture, brewery, chemical/paints, food and beverages,
healthcare, industrial/domestic products, and petroleum sub-sectors respectively in which a
negative relationship between CG and DPs is observed should maintain a regular and steady
increase in their dividend payment so as to maximise shareholders’ wealth and improve welfare of
other stakeholders. In addition, policy makers especially, Security and Exchange Commission
(SEC) in connection with the Nigerian Stock Exchange should provide needed interventions to
these subsectors so that their CG can be enhanced. More independent directors should be on the
boards of corporate firms and the proportion of institutional shareholding should also be increased
to improve monitoring.
Third, our results show that CG does not impact DPs of agriculture subsector. The
prevalence of environmental factors associated with the subsector might be part of the explanation
of the cause: agriculture subsector has been neglected for decades. Institutional shareholders and
independent directors that might have promoted innovations and growth in the subsector have
shied away from it, hence, food insecurity remains a concern in the country. For Nigeria to
contribute to feeding Africa, government of Nigeria should intensify efforts in ensuring that
Nigerian agriculture & Agro-Allied subsector is assisted so that it can better be performing,
enhance its returns thereby attracting more investors to the industry and consequently creating a
vicious cycle. The government of Nigeria through the Ministry of Food and Agriculture should
encourage youth participation in the agricultural sector. The sector offers career opportunities in
research, environment, financial management and other technical areas for the youth to explore
for higher productivity.
Fourth, in addition, Nigerian capital market regulatory authorities should ensure that
corporate firms strictly comply with the codes of CG to minimise market infractions and promote
investment in the financial sector. When this is done, local and foreign investors will be motivated
to come to the market; more equity financing will be harnessed with dynamic growth which
invariably will lead to more job creation.
Fifth, Nigerian corporate firms should disclose more governance information in their
annual reports and statements of accounts so that prospective researchers and investors (local and
foreign) could evaluate them adequately for more rigorous research and portfolio management
respectively.
Lastly, looking ahead, it is obvious from the discussions and findings of this study that the
Bilateral and Multilateral Development Partners (especially the AfDB) development priorities and
24
policy dialogue with its Regional Member Countries (RMCs) should be consistently anchored on
good governance trajectory. This imperative intervention from the Bank and other development
partners is more evident in the agriculture and petroleum subsectors. Specifically, CG should
continue to be taken into account in their investment allocations not only to the firms in the capital
markets considered in this study but also public sector operations. Indeed, the African
Development Bank Group – in line with its Ten Year Strategy 2013–2022 and the reinforced
priorities, that is the High 5 priority areas5 has the potential to improve CG through improved
financing, technical assistance, capacity building, knowledge generation and uptake for
stakeholders in the capital market.
5 “High-fives” Application
25
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