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

4

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.

5

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.

6

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

7

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

8

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

9

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

10

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

11

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.

12

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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33

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