Dynamic Interactions in the Nexus Among Dividend,Firms’ Investment Behaviour and Value of Selected Quoted Companies in Nigeria (2001

Abstract

In this article, we investigated the dynamic interactions in the nexus among dividend pay-out policy, investment behaviour and the value of listed companies in Nigeria from 2001 to 2019. Structural vector autoregression modelling framework, was employed as technique of analysis. The study employed annual data of listed firms on the Nigerian Stock Exchange. Data were sourced from the annual reports and accounts of the firms and the fact books published by the Nigerian Stock Exchange. The results revealed that investment policy and market value responded gradually to temporal and permanent shocks in the dividend decisions of companies. The study, therefore, recommended that the reaction of investment policy and the market response to variations in dividend policy were contractionary which could then enhance investment decisions and the market values of quoted companies in Nigeria.

Keywords

Dividend pay-out investment behaviour value structural vector autoregressions non-recursive restrictions impulse response Nigeria

Introduction

Dividend decisions are important in corporate finance because they are one of the three major dynamic pillars of corporate organizations. Financing and investment decisions are the other two important decisions made by finance managers in corporate firms. Dividend policy is the process of selecting the right percentage of a corporation’s earnings to be dispersed as cash dividends to equity holders in the organization, as well as financing feasible investment possibilities. Given the prevalence of agency relationships and conflict in corporate organizations, a steady progression of cash dividend payments will serve as a signal to financial supporters that the governance of the companies is performing admirably.

Almost, every one of the theoretical and exact examinations that have widened our comprehension of dividend pay-out dynamics since the 1960s owes a scholarly obligation to the notable work of Miller and Modigliani (1961). They concluded at the time that companies’ management could not impact firms’ value and investment openings by changing its dividend policy strategy. In this manner, they believed that dividend policy is simply insignificant when capital markets are perfect, an idea that seems, by all accounts, to be a hallucination and opposing to genuine circumstances (Megginson et al., 2007). Perhaps, dividend pay-out dynamics were likewise viewed as a puzzle at that time, because company management could not influence firm value and investment opportunities by modifying its dividend policy (De-Angelo & De-Angelo, 2006). Generally, an organization’s investment pattern has a significant impact on its dividend policy. Some scholars had argued that corporate investment opportunity sets and dividend policy are mutually exclusive since both contest the firm’s available finite resources (Aretz & Bartram, 2010; Ardestain et al., 2013).

The global recession of 2007–2009 and that of 2012 had serious impacts on Nigeria’s general economy and, in particular, the securities exchange. During this time, the market capitalization and all-share index declined drastically and trading activities dwindled by over 80% (Onaolapo et al., 2013). All of these culminated into loss of investors’ confidence as there was a mass exit of foreign players in the exchanged markets (Onaolapo et al., 2013), and many local investors also, divested their interests due mainly to sluggish demand, general fear and uncertainty that accompanied the recessionary period (Ijeoma, 2017). Regardless of the current uptick in productive events, many businesses are still dealing with the outcomes of the recession. There were also indications of a decline in the number of companies paying dividends and the propensity of companies to pay dividend in Nigeria. This may be a result of harsh economic conditions, global and local recession, socio-political problems and a bearish hold of the stock market which negatively affected the business environment in which the companies operated and consequently the performance of companies during these periods. This implies that Nigeria, like other African countries, also experienced economic challenges which affected the business environments thereby reducing the payment of dividend to investors. There is, therefore, a need to investigate the link between dividend pay-out policy, business investment behaviour and corporate value.

Contrary to other empirical pieces of work on dividend policy strategy, this study contributes to the extant literature in two ways. First, it investigates how the dividend, firms’ investment behaviour and value of quoted companies reacted to discrete ephemeral and perpetual shocks. This is viewed as a virgin region, as no realized investigation has at any point been directed on this, in Sub-Saharan Africa (and Nigerian in particular). The reason of zeroing in on Nigeria, emerged from the fact that there are laws, standards, corporate culture and qualities faithful to her. Accordingly, this idiosyncrasy of the Nigerian business climate further requires a material comprehension of the linkage between dividend pay-out policy, firms’ investment behaviour and the value of quoted companies in a, particularly emerging market. Second, this work employs structural vector autoregression (SVAR) technique in achieving the objective of the study. SVAR is an adaptable strategy explicitly for the investigation of policy action on the real economy and changes in business cycles. SVAR procedure is a refined device and advancement that are recognized through exclusionary restrictions which are essential to the development of a model that is utilized for policy investigation and forecasting purposes. The strength of SVAR over the conventional vector autoregression (VAR) models is that results are uncovered by huge and confounded structures. Additionally, as indicated by Sims (1980), it gives an efficient way to deal with forcing limitations either through hypotheses or by instincts, which empowers experts to catch experimental consistencies which are hidden in the conventional VAR.

Ultimately, these aforementioned focusses examine to be novel and it is believed that the general outcomes would propose how companies’ market value and performance will respond to the investment and dividend policy of quoted companies in Nigeria.

Literature Review

Theoretical Issues

Corporate financial theory has a lot to say concerning the dynamic link between dividend, investment policy and the market value of the company. Taking an all-inclusive view on the subject of discourse, however, what the theory has been saying is not only ambiguous, but also conflictual. So many theories and studies have explored and emphasized different channels (Leahy & Whited, 1996). Some introduced a negative relationship, while some others announced a positive relationship. Given these theoretical models and empirical contentions, it is as yet astonishing that little exact work has been done on the dynamic associations among dividends, investment policy and the value of companies. Current examination on dividend pay-out policy thus revolves around the firms’ ideal strategy for dividend pay-out policy, the reaction of the market to firms’ dividend decisions, signalling hypothesis, the clientele effects, taxation issues associated with dividend and capital gains, the relevance of agency cost, life cycle theory of dividend and the drivers of dividends (Asadi & Oladi, 2015). From modern empirical and theoretical work on dividend policy, three dominant views can be inferred. The first one is the traditional view who asserted that dividend policy and behaviour are irrelevant to the value of companies. That is, the dividend pay-out policy a company pursues and the value of that company moves in parallel directions (Modigliani & Miller, 1958; Meyers & Allen, 2010). While the conservative group asserted that corporate dividend policy has an upward influence on the stock prices of the company and that an increase in dividend payment increases the share value of the company (Al-Makuni, 2007; Bali, 2003; Bhattachaya, 1979; Gordon, 1963; Lease et al., 2000; Litner, 1962; Miller & Rock, 1985). This school of thought believed and proposed that companies should pursue an aggressive and active dividend policy to enhance the market value of such companies. This position has often and severally been criticized, in that companies may lose viable investment projects due to a cash crunch arising from huge payments of dividends every financial year. Moreover, companies that pursue this policy may resort to depleting the equity reserves of the companies or to borrowing to raise funds to pay dividends at the end of the financial year. The last group which is called the radical group believed that higher dividend pay-out and firms’ value move in opposite directions and that an active pay-out will deteriorate the value of the company (Litzenberger & Ramaswanzy, 1979). This school of thought further advanced that an aggressive dividend policy in a corporate organization may imply that there are no profitable investments to be undertaken, while in contrast, a residual dividend policy may imply that the firm is retaining funds for growth opportunities and business expansion (Sofer et al., 1996; Woolrige & Gosh, 1985).

Also, important elements of the market value of firms are the investment opportunity sets open to it (Ardestani et al., 2013). Corporate investment opportunities are viable projects that firms discover and utilize for economic gains (Myers, 1977), and they entail using capital expenditure to make new products or better still for business expansions and growth opportunities (Kallapur & Trombley, 2001). Investment opportunity sets astonishingly inspire the perspective of the stakeholders of the company about the stock values, as it is believed that viable investment opportunities tend to increase the share price of the firm in the long run, even though the firm may have a low level of income at the moment (Ardestani et al., 2013; Artez & Bartram, 2010; Kallapur & Trombley, 2001). Thus, it is asserted in the extant literature that corporate investment affects the dividend policy of firms (Abbott, 2001; Ardestani et al., 2013; Artez & Bartram, 2010).

Conversely, some authors have also put it forward that corporate investments and dividend pay-out policy are two parallel lines that may never meet. This is because both dividend policy and investment compete for the available cash resources of the firm, and therefore organizations may want to cut down on the pay-out to have enough funds to finance growth expansions and business opportunities. It is even believed that it is when firms do not have enough viable investment opportunity sets or there are negative net present value projects that companies pursue an active dividend pay-out (Black, 1976; Fairchild et al., 2013; Gaver & Gaver, 1993; Jones & Sharma, 2001; Smith & Watts, 1992; Subramanian et al., 2011).

Empirical Issues

The outcome of a study by Al-Hares et al. (2012) shows that dividends are significantly related to share price when substituted for earnings in the valuation model. The investigation utilized the price valuation model where firm worth is stated as a linear function of share book value, earnings and net investor cash flows. While the income to stockholders is thought to be subsumed in the earning term, due to multicollinearity issues among dividend and earnings, the dividend was discarded in the equation. The impact of dividend announcement on the stock returns of the chosen companies was examined by employing generalized autoregressive heteroscedasticity (GARCH). Tsai and Wu (2014) re-examined the information content of dividend declarations in India from 2012 to 2014. The study utilized exhaustive transaction data from Trade Reporting and Compliance Engine (TRACE) to consider the reaction in the corporate security market and dividend declaration. They discovered the connection between the magnitude of dividend fluctuations and future performance to be scrawny.

The relationship between institutional investment horizons and dividends in the UK is explored by Erhan and Ozgur (2017). Institutional investors with higher Churn rates are transient investors while the long-term institutional investor has a positive impact on dividend choices. The analysis revealed that there is a significant inverse relationship between the Churn rate and cash dividend, which infers that momentary institutional investors negatively affect dividend while long-term institutional investor has a positive effect. Yeo (2018) examined the influence of cash flow on the level of investment and dividend. The study discovered that free income free cash flow (FCF) sways investments and dividends where high FCF builds investment opportunity sets and decreases dividends. Yeo concluded that the presence of FCF vulnerability in shipping firms tends to cut dividends to maintain the investment, hence a negative relationship between leverage and investment.

Data zeroed in on dividend behaviour of listed firms in the UK between 1997 and 2012 sourced from six distinct sources are specific Compustat Global, Datastream, Zephyr, Fame, I/B/E/S and Bordeaux. Driver et al. (2020) censured the presumption of agency theory that managers have an inclination for retention which results in over-capitalization or misdirected investment opportunities. They additionally checked how pressures on investors work through acquisitions activity, corporate governance and investor trading behaviour. Danso et al. (2019) examined the link between CEOs’ market soppiness and investment in US firms under the contention that managerial decisions are influenced by psychological or potentially intellectual inclinations. The study upholds the contention CEO cognitive and cognitive biases impact the corporate choices of the firm yet discovered no proof that financial adaptability matters in the sentiment–investment association. This is although human conduct influences investment choices and investors, as a rule, settle on choices during risky and confounded conditions dependent on sentiments and intuitions (e.g., past experiences, trends and patterns), rather than equitably dissecting the accessible information available to them (Parveen et al., 2020). Heuristics and preconceptions influence the choices of investors on investment in the Pakistan stock market. This behaviour is alluded to as Heuristics conduct which the investigation of Parveen et al. (2020) revealed. They developed a theoretical model that shows the linkage among various predispositions and their joint impact on the investment choices of Pakistan investors.

The impact of IFRS on the compelling impact of dividend decisions on corporate investment can result from uneven information access among the treated and control groups. A study by Harakeh (2020) used a difference-in-difference research design test to appraise the impact of information tremor on the extent of information disparity. They thereafter gave proof that recommended results for IFRS adoption in the capital market could be realized as a result of their adoption. Yao et al. (2020) examine the effectiveness of China’s semi-mandatory dividend policy. They found out that the new policy has significantly increased investor trust and certainty, da Silva (2020), meanwhile, investigates whether stock prices influence the relationship between investment and stock. The study found a positive relationship between stock prices and investment, as well as evidence that the measure of private information included in share price data enhances future benefits.

Tekin and Polat (2020) made a comparative analysis of the dividend policy of firms in the UK. Data for the analysis was gathered from Worldscope in DataStream worldwide from 2002 to 2017. Their outcome showed that during the financial meltdown, MAIN firms diverted their internally generated funds to different sources as opposed to bordering over the reduction of the adverse consequences in dividend payment would bring about. They additionally showed that the two markets abruptly utilized dividends. Yarba and Yassa (2021) examined public and private firm investment behaviour from the year 2006 to 2018 in Turkey. Their study was driven by the equivocalness related to the effect of stock market listing on corporate investment. Their findings align with the extant literate that public firms accomplish higher growth and put commits investment more than private firms.

Contrary to previous empirical investigations on the effects of dividend decisions and investment policy on various corporate characteristics (like market reactions, earning quality, performance, size etc.) as discussed in the empirical survey above, this study examines the impact of external shocks on each of the components of major corporate characteristics which are specifically dividend decisions, investment policy of the firms and the market value. This is because the period covered in this study involves major events and policies like bank recapitalizations and consolidations policy in 2005, the general elections in 2003, 2007, 2011, 2015, and in year 2018, slump in the price of crude oil in year 2014 and 2015, and the recession of 2007 and 2012. There were also socio-political problems, security challenges and the bearish hold of the stock exchange. All of these events created a harsh business environment for corporate organizations to thrive which also eroded the investors’ confidence, as most foreign investors had to divest their interest in major companies in Nigeria. So, investigating the external shocks on dividend decisions, firms’ investment behaviour and value will help to decipher how these core variables in corporate organizations responded to variations in one another. The SVAR is thus applied to focus on non-recursive contemporaneous restrictions, and the impulse response analysis. Also, the inclusion of lags of independent variables which is the major specification of VAR modelling framework, corrects for problem of endogeneity which might be as a result of omitted variables, firms’ heterogeneity and measurement errors. The lag selected criteria are then conducted to know the exact lag length in the model specification.

Data Description

In evaluating the dynamic link between dividend pay-out policy, firms’ investment behaviour and value, this work started the examination with the descriptive investigation as portrayed in Table 1. An undeniable degree of consistency was shown by the firms’ data series in Table 1. As their mean and median fall inside the scope of least and greatest upsides of the series. For example, the mean value of dividend per share (DPS) remained at 0.55, which suggests that the vacillation in DPS was negligible over the time of the study. The standard deviations of DPS and market value (scaled by Tobin’s Q) were fairly low demonstrating that deviations of the real data from their mean qualities were little.

Notwithstanding, the standard deviation of the investment (proxied by property plant and equipment (PPE)) was 9.5E+08, showing unsteadiness when contrasted with other variables. Descriptive analysis additionally, uncovered that every variable of interest was positively slanted and leptokurtic (slanted) compared with normal distribution. At last, the likelihood that the Jarque–Bera measurements surpass (in absolute terms) the observed value is by and large low for all the series. This, consequently, suggests the dismissal of normal distribution at 5%.

Table 1.

Descriptive Statistics of Data Series for the Dynamic Relationship Among Dividend Policy, Firms’ Investment Behaviour and Value of Quoted Companies.

Variables	DPS	PPE	TQ
Mean	1.040500	2.62E+08	1.788933
Median	0.550000	64,10631.	0.929576
Maximum	12.11687	1.40E+10	821.8670
Minimum	0.000000	1,192.000	0.000000
Std. dev.	1.326363	9.56E+08	23.12741
Skewness	2.336041	6.563465	35.37053
Kurtosis	13.83046	61.80951	1,254.706
Jarque–Bera	7,315.770	190,923.5	82,649,081
Probability	0.000000	0.000000	0.000000
Sum	1,313.111	3.30E+11	2,257.634
Sum sq. dev.	2,218.399	1.15E+21	674,479.9
Observations	1,600	1,600	1,600

Source: Author’s computation (2021).

Note: DPS: Dividend per share; PPE: property plant and equipment; LGE: listing age; TQ: Tobin’s Q.

Table 2.

Correlation Matrix of Data Series for the Dynamic Relationships among Dividend Policy, Firms’ Investment Behaviour and Value of Quoted Companies.

	DPS	PPE	TQ
DPS	1.000000
PPE	–0.026678	1.000000
	(–0.947304)
TQ	0.014521	–0.010368	1.000000
	(0.515497)	(–0.368043)

Source: Author’s computation (2021).

Note: This table shows the relationship among the variables used in the study. For most of the variables, the results showed a weak relationship. Values in parenthesis are probability values.

Correlation coefficient matrix on Table 2 Inspected the conceivable level of relationship among the variables. Results showed the connection coefficients and the bearings of the relationship among the variables. The measure of the investment (e.g., PPE) and the DPS uncovered a negative relationship among them. While DPS showed a positive relationship with the measure of market value (e.g., ’Tobin’s Q). The matrix additionally showed that all variables do not have a strong relationship with ’Tobin’s Q. Hence, the relationship network as portrayed in Table 2 Has shown fascinating outcomes on the connection among reliant and autonomous variables employed in the study. However, one needs to be careful in interpreting results on the correlation coefficient. The basic bivariate relationship grid in Table 2 just depicted the degree of a direct connection between sets of variables utilized in this work. Additionally, the connection between these variables of interest does ’not suggest causation. In this manner, the positive or negative relationship coefficient revealed in Table 2 Just shows the degree of the linear connection between sets of variables utilized.

Research Methods

This research work tested eighty listed firms on the Nigeria Stock Exchange from the year 2001 to 2019. The data for this work were gotten from the audited yearly reports and records of the chosen quoted companies on the Nigerian Stock Exchange and also the fact book published by the Nigerian Stock Exchange. The rationale behind this is that the selected firms were in existence all through the assessment period, and their data are instantly open and accessible.

In order to achieve the objective of this study, the SVAR model was specified to show the dynamic relationship among the variables of interest. This was estimated using contemporaneous matrix and impulse response functions. In estimating the dynamic relationship between the dividend pay-out policy, ’Firms’ investment behaviour, and the value of listed companies in Nigeria, this research work began analysis, by first carrying out the preliminary tests, which include the descriptive statistics, the correlation matrix and the unit root tests. A non-recursive scheme matrix analysis was carried out, then an optimal lag selection was also done for the dynamic SVAR system, to cater for short lags and the omitted variables. After these, SVAR estimates were carried out and interpreted and the estimated parameters were determined for the non-recursive restrictions placed on the short run pattern matrix B. Following these, the SVAR variance decomposition was determined, analysed and interpreted, and the impulse response function graphs were also plotted and interpreted. A stability test was also carried out using inverse roots of AR characteristics of polynomial, to decipher the stability of the estimated SVAR results.

Model of Dynamic Relationship among Dividend Pay-out Policy, Firms’ Investment Behaviour and Value

{DP}_{i t} = α_{i j} + \sum_{j = 1}^{n} α_{11 i j} {ΔDP}_{i t - j} + \sum_{j = 1}^{n} α_{12 i j} {INV}_{i t - j} + \sum_{j = 1}^{n} α_{13 i j} {FV}_{i t - j} + u_{i t}

(1)

{INV}_{i t} = Φ_{i j} + \sum_{j = 1}^{n} Φ_{11 i j} {ΔINV}_{i t - j} + \sum_{j = 1}^{n} Φ_{12 i j} {DP}_{i t - j} + \sum_{j = 1}^{n} Φ_{13 i j} {FV}_{i t - j} + u_{i t}

(2)

{FV}_{i t} = ψ_{i j} + \sum_{j = 1}^{n} ψ_{11 i j} {ΔFV}_{i t - j} + \sum_{j = 1}^{n} ψ_{12 i j} {DP}_{i t - j} + \sum_{j = 1}^{n} ψ_{13 i j} {INV}_{i t - j} + u_{i t}

(3)

where

DP = the dividend policy.

INV = investment behaviour.

FV = firms’ value.

Dividend policy is proxy by DPS; investment behaviour is proxy by capital expenditure on property, plant and equipment, while firm value is measured by Tobin’s Q model. Equation (1) explains how the firms’ investment behaviour and firms’ value reacted to shocks in dividend policy of the companies. Equation (2) explains how the dividend policy and firms’ values responded to shocks in the firms’ investment behaviour and Equation (3) explains how firms’ investment behaviour and dividend policy reacted to shocks in the firms’ value. Therefore, Equations (1)–(3) capture the dynamic interaction in the nexus among the dividend policy, firms’ investment behaviour and firms’ value.

However, due to the nature of the variables of interest and the need to show the interaction among dividend policy, firms’ investment behaviour and corporate value, the model specified was estimated using SVAR technique. The stability test was done to ensure the usage of the model for policy formulation and implementation by Nigerian quoted firms and the government. However, if the variables were found co-integrated, the model would have been estimated using the structural vector error correction model (SVECM), which is a variant of SVAR.

Therefore, Equations (1)–(3) were transformed and re-specified as follows in equation (4).

In the model, $α_{0}, Φ_{0} {and Ψ}_{0}$ are constant terms, respectively, while, $α_{1} - α_{3}, Φ_{1} - Φ_{3} {and Ψ}_{1} - Ψ_{3}$ were coefficients that were estimated, respectively. ∇ represents the first difference operator. $U_{1 i t} - U_{3 i t}$ are mutually uncorrelated stochastic error terms with finite covariance matrix and zero mean, t is the period (years) that ranges from 1, 2, …, 19, i is the cross-section (firm) that ranges from 1, 2, …, 80 and j is the lag length.

[\begin{matrix} {ΔDP}_{i t} \\ {ΔINV}_{i t} \\ {ΔFV}_{i t} \end{matrix}] = [\begin{array}{l} α_{0} \\ Φ_{0} \\ Ψ_{0} \end{array}] + \sum_{i = 0}^{n} [\begin{matrix} α_{1 i} & α_{2 i} & . & \dots \dots \dots & α_{5 i} \\ Φ_{1 i} & Φ_{2 i} & .. & \dots \dots \dots & Φ_{5 i} \\ Ψ_{1 i} & Ψ_{2 i} & .. & \dots \dots \dots & Ψ_{5 i} \end{matrix}] [\begin{matrix} {ΔDP}_{i (t - j)} \\ {ΔINV}_{i (t - j)} \\ {ΔFV}_{i (t - j)} \end{matrix}] [\begin{matrix} U_{i t} \\ U_{i t} \\ U_{i t} \end{matrix}]

(4)

Empirical Analysis

Results

We started our estimation with a unit root test. This was additionally performed for the variables of interest in the assessment of the dynamic link between dividend policy, investment and values of the chosen quoted Nigerian companies. This test was done as a result of the issue of the non-stationarity nature of time-series data, which must be taken into consideration in the estimation process, so as not to get false regression analytical results with grave negative effects on business and public strategies. Two techniques of the unit root test were employed as depicted in Table 3. The outcome of the panel unit root test, both with pattern and without pattern showed that every one of the three variables was stationary at levels and were all significant at 1%. Thus, this work dismisses the null hypothesis of a unit root.

Table 3.

Unit Root Test for the Dynamic Relationships among Dividend Pay-out Policy, Firms’ Investment Behaviour and Value of the Sampled Companies.

Variables		Levin et al.		Im et al. (2003)
	With Trend	Without Trend	Levels	With Trend	Without Trend	Levels
DPS	–4.58060*	–3.98894*	I(0)	–2.51588*	–3.74021*	I(0)
PPE	–9.00109*	–10.6323*	I(0)	–4.25641*	–8.46060*	I(0)
TQ	–11.4822*	–15.0854*	I(0)	–8.16482*	–14.1550*	I(0)

Source: Author’s computation (2020).

Note: *Indicates the level of significance at 1%.

Estimation of Dynamic Relationship Among Dividend Pay-out Policy, Firms’ Investment Behaviour and Value of Quoted Firms in Nigeria

In estimating the dynamic process in this study, Equations (1)–(4) were formulated. To achieve identification in the SVAR, this study adopted the non-recursive scheme, being guided by Kim (1999) and Holtermoller (2002). Matrix B on Table 4 is a diagonal and of order 4 × 4, which has the following structure as depicted in Table 4.

Table 4.

Matrix B.

	DPS	PPE	TQ
DPS	1	*	*
PPE	*	1	0
TQ	*	0	1

Source: Author’s computation (2021).

Note: *Signifies freely estimated parameters.

The identification scheme above is over-identified with six restrictions and the asterisk (*) signifies freely estimated parameters. The first line represented the reaction response of firms’ investment behaviour (proxied by PPE) and market value proxied by (Tobin’s Q) to corporate dividend policy (also proxied by DPS). The second line represented the response of dividend policy to investment behaviour of the firm, while the third line incorporated the hypothesis of dividend signalling theory; that the market value of a firm responds to the dividend policy the company operates.

Another crucial issue of concern is the appropriate selection of the optimal lag for the SVAR. Excessive short lags may not capture the dynamics of the SVAR system, which could subsequently lead to omitted variables, prejudice remaining coefficients and the likelihood of producing serially correlated errors. Conversely, lengthy lags lead to a rapid loss of a degree of freedom and over-parameterization (Apanisile & Akinlo, 2013; Gujarati & Porter, 2009). The length of the lag structure for the models was empirically determined using various information criteria. Two lags were found to be the optimal structure that the model could accommodate. The results of the lag selection criteria were presented in Table 5. The results showed that Schwarz information criterion (SIC) was found superior to other specifications as indicated by all criteria. As a result, all other analyses in the study were carried out using SIC.

Table 5.

Optimal Lag Selection.

Lag	LogL	LR	FPE	AIC	SC	HQ
0	–26,550.86	NA	1.62e + 21	57.35174	57.36739	57.35771
1	–25,863.76	1,368.258	3.75e + 20	55.88717	55.94977	55.91105
2	–25,779.25	167.7521	3.19e + 20	55.72407	55.83363*	55.76587
3	–25,765.92	26.36050	3.16e + 20	55.71473	55.87124	55.77444
4	–25,744.11	43.00321*	3.07e + 20*	55.68707*	55.89053	55.76469*

Source: Author’s computation (2021).

Notes: *Indicates the lag order selected by each criterion; LR: sequential modified LR test statistic (each at 5% level of significance); FPE: final prediction error; AIC: Akaike information criterion; SIC: Schwarz information criterion; HQIC: Hannan–Quinn information criterion.

Structural Vector Autoregression Estimates

Table 6 showed the results of the vector autoregressive model of the dynamic relationship among dividend policy, firms’ investment behaviour and the value of some selected quoted companies in Nigeria. The results, as shown in Tables 7 and 8 revealed the estimated parameters of the variables under consideration with their standard errors. It was discovered that the response of firms’ investment behaviour (proxied by PPE) to any shock in corporate dividend policy (proxied by DPS) was negative and will reduce by 0.328127% at a 1% level of significance. The response of market value (proxied by Tobin’s Q) to shocks in firms’ investment was positive and would increase by 26.93% at a 1% level of significance also.

Table 6.

Short-run Pattern Matrix B.

	DPS	PPE	TQ
DPS	1	C (3)	C (4)
PPE	C (1)	1	0
TQ	C (2)	0	1

Source: Author’s computation (2021).

Table 7.

Estimated Parameters for Matrix B.

	Coefficient	Std. Error	z-Statistic	Prob.
C (1)	–0.328127	0.013759	–23.84768	0.0000
C (2)	26.93995	0.554307	48.60115	0.0000
C (3)	–2.009786	0.031206	–64.40369	0.0000
C (4)	–1.020154	0.022078	–46.20667	0.0000
Log-likelihood	–7,749.550
LR test for over-identification:
Chi-square (2)	3,008.142		Probability	0.0000

Source: Author’s computation (2021).

Table 8.

Estimated Matrix B.

	DPS	PPE	TQ
DPS	1.000000	–2.009786	–1.020154
PPE	–0.328127	1.000000	0.000000
TQ	26.93995	0.000000	1.000000

Source: Author’s computation (2021).

However, the proportionate response of dividend pay-out policy (i.e., DPS) to tremors in firms’ investment (PPE) also appeared negative and would decrease by 2.0097% at a 1% level of significance as depicted in Table 6. While the response of market value (i.e., Tobin’s Q) to tremors in dividend policy (i.e., DPS) was also negative and reduced by 1.02015% and also significant at 1% level.

Discussion of Findings

Impulse Response Analysis

The impulse response function is also adopted in the study to examine how each of the variables of interest adjusts in response to any shock in the other variables. The impulse response function described the reaction of one variable to the innovations in another variable in the system while holding all other palpitations equal to zero.

The diagram depicted in Figure 1 showed that the response of dividend policy to unanticipated shocks in the firms’ investment (PPE) was negative and was a little bit below the zero lines as from the first period implying a negative response to palpitations in the investments of the companies. It, however, began to track the zero line from the second period to the fifth period. This showed that dividend policy became insensitive to shocks in firms’ investment policy in the short run. It began to respond positively but very gradually as from the second period. Figure 1 then revealed that as from the sixth period, the response of dividend policy began to rise above the zero lines, thereby depicting a positive response to the shocks in firms’ investment and the response seemed constant till the 1oth period. This thus implied a positive response to unanticipated shocks in investments policy in the long run.

The response of dividend policy of quoted companies to the market values as depicted in Figure 1 was nil in the 1st period and thus began to rise positively in the 2nd period, but reacted spontaneously in the 3rd and 4th periods. The response to shocks in the market value dropped a bit in the 5th period and then maintained a steady response in the 6th, 7th, 8th, 9th and 10th periods. This then clearly showed that companies used an active and aggressive dividend policy to enhance the market value of the companies. This is in line with the work of Lease et al. (2000), Bali (2003), Al-Malkawi (2007) and Kajola and Desu (2015).

Figure 1 also revealed the response of firms’ investment to shocks in corporate dividend policy. The response of firms’ investment was zero in the 1st period and it began to respond sharply but inversely as from the 2nd period till the 10th period. The implication of this is that the investment of corporate organizations began to wane and reduce when companies began a campaign of active dividend policy or when companies pay steady and high amounts of companies’ profits to shareholders year in and year out. This also means that viable investment opportunities will be left unattended unless the companies rely on external means of financing such as public offers, private placement, debt financing among others. This may subsequently lead to dilution of control, a high level of gearing and a high level of financial risk.

The response of firms’ investment to the market value (proxied by TQ) was also very spontaneous and negative from the first and second periods of the forecast horizon. This may be as a result of the recessionary period when the stock market plummeted and the stock value reduced drastically, which also discouraged corporate investment behaviour. Hence, corporate organizations became sluggish, waiting for possible improvements in the capital market before taking any investment decisions. The response of firms’ investments to shocks in market value became stable from the 3rd period to 7th period and it rose a little from the 8th period to 10th period.

The response of market values (TQ) to unanticipated shocks in the dividend policy of quoted Nigerian companies was also depicted in Figure 1. The impulse response graph in Figure 1 showed that market values (TQ) responded sharply, instantaneously and positively to variations in the dividend policy of the companies in the first to third periods. This showed that capital markets participants were favourably disposed to companies with high dividend pay-out in the short run, hence the enhanced market value. This also supported the claims of authors, such as Bhattacharya (1979), Kajola et al. (2015) and Aqel (2016). However, the response of market values of companies experienced a little wane in the 4th period and then maintained a steady response from the 5th to 10th periods. This thus indicated that corporate dividend policy may not necessarily have so much influence on the market values of companies in the long run.

Also, from the diagram depicted in Figure 1, the response of market value to unexpected shocks in the firms; investment (PPE) was positive in the first period, but fell drastically as from the second period and then began to track the zero line afterward. The implication of this is that the market value of quoted companies responded greatly to the unexpected shocks in the firms’ investment behaviour in the short run, that is, the first and second periods of the forecast horizon but began to diminish and also became minimal in the long run.

To test for the stability of the model for the SVAR results of the dynamic relationships among dividend pay-out policy, firms’ investment behaviour and value of selected quoted companies in Nigeria, the inverse root of AR characteristics polynomial was adopted. The roots view displayed the inverse roots of the AR and/or MA characteristics polynomial. The graph view plots the roots in the complex plane where the horizontal axis is the real part and the vertical axis is the imaginary part of each root. If the AR root lies within the unit circle, then the estimated SVAR result is stable. If otherwise, it is unstable. The stability test result implies that it is valid. Figure 2 shows that the SVAR result is stable and valid because all roots fall within the circle.

Conclusion and Policy Recommendations

The essential issues encompassing the proportionate responsiveness of the value of quoted companies in Nigeria to inherent perpetual and transient shocks in dividend decisions and investment policy of firms in Nigerian have been entirely explored in this study. Additionally, the utilization of the SVAR models intending to the examination issue have been very natural, robust and exceptionally proper. The exact outcomes then, at that point illuminated the dynamic link between corporate dividend policy, firms’ investment behaviour and value of listed companies in Nigerian which additionally gave a solid premise whereupon the business and financial policies can be defined, assessed and observed.

The outcome of the dynamic examination showed that the reaction of firms’ investment behaviour and dividend decisions to vicissitudes in the market value of quoted companies in Nigeria was positive and significant, the response of market value and dividend pay-out to erraticism in investment opportunity sets in listed companies in Nigerian were progressive but positive simultaneously, while the response of dividend policy was spontaneous. The responses of firms’ investment and market value to innovation shocks in dividend policy were also positive and significant. However, this study shows that firms’ investments responded a great deal to variances in the dividend policy of quoted companies in Nigeria.

Hence, from the findings in this study, the policy recommendations in this regard are as follows:

During periods of economic buoyancy of firms in Nigeria, management should embark on an active dividend policy as this will create a favourable image for the companies in the stock markets and also enhance the market values.

Furthermore, findings revealed that firms’ investments responded spontaneously and positively to shocks in dividend pay-out. The policy implication in this regard is that firms will be motivated to increase investments in profitable projects. Thus, the federal government through its monetary authorities is therefore encouraged not to always tighten monetary policy, because of its spillover effects on the companies’ liquidity as well as investment decisions of firms in Nigeria.

Although the distribution of dividends to investors serves as signals about the performance of companies in the capital markets, its interaction with investments exhibits a negative impact on the values of quoted companies in Nigeria. This shows that firms’ cash flows in terms of dividend payment/pay-out and investment at the same time, contradict the market value improvement of the firms. As a result of this, there are tendencies that stock market activities regarding the market value of the companies’ shares may not be encouraging to the extent of attracting higher values because of the investment and dividend situation of the sampled Nigerian companies within the period of the study. It is, therefore, recommended that the company should have the policy to retain shareholders that decided to stay with the company at the period when investment and dividend activities are undertaken pari passu. This policy can be in the form of the right issue to existing shareholders.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

ORCID iD

John Ayobamibo Olayiwola

References

Abbott

(2001). Financing dividend and compensation policies are subsequent to a shift in the investment opportunity set. Managerial Finance , 27(3), 31–47.

Al-Hares

O. M.

, AbuGhazaleh

N. M.

, & Haddad

A. E.

(2012). Value relevance of earnings, book value and dividends in an emerging capital market: Kuwait evidence. Global Finance Journal , 23, 221–234.

Al-Malkawi

(2008). Factors influencing corporate dividend decision: Evidence from Jordanian panel data. International Journal of Business , 13(2), 12–30.

Al-Malkawi

N. H.

(2007). Determinants of corporate dividend policy in Jordan: An implication of Tobit Model. Journal of Economic and Administrative Sciences , 23(2), 44–70.

Apanisile

O. T.

, & Akinlo

(2013). Rail transport and economic growth in Nigeria. Australian Journal of Business and Management Research , 3(5), 18–24.

Aqel

(2016). An empirical investigation of corporate dividend payout policy in an emerging market: Evidence from Palestine Securities Exchange. Research Journal of Finance and Accounting , 7(6), 7–16.

Ardestani

H. S.

, Rasid

A. S.

, Basieuddin

, & Mehri

(2013). Dividend payout policy, investment opportunity set, and corporate financing in the industrial products sector of Malaysia. Journal of Applied Finance and Banking , 3(1), 124–138.

Aretz

, & Bartram

(2010). Corporate hedging and shareholder value. The Journal of Financial Research , 33(4), 317–371.

Asadi

, & Oladi

(2015). Dynamic determinants of dividend in affiliated and unaffiliated companies to the government in the Tehran Stock Exchange (TSE). Iranian Journal of Management Studies (IJMS) , 8(1), 91–100.

10.

Bali

(2003). An empirical analysis of stock returns around dividend changes. Applied Economics , 35, 51–61.

11.

Bhattacharya

(1979). Imperfect information and dividend policy and the bird in the hand fallacy. The Bell Journal of Economics , 10, 259–770.

12.

Black

(1976). The dividend puzzle. Journal of Portfolio Management , 3, 5–8.

13.

Danso

, Lartey

, Amankwah-Amoah

, Adomako

, & Lu

(2019). Market sentiment and firm investment decision-making. International Review of Financial Analysis , 66, 1–16.

14.

daSilva

P. P.

(2020). Do managers pay attention to the markets? A review of the relationship between stock price informativeness and investment. Journal of Multinational Financial Management . https/doi.org/10.1016/J.MulFin.2020.100675

15.

De-Angelo

, & De-Angelo

(2006). Dividend policy and the earned/contributed capital mix: A test of the lifecycle theory. Journal of Financial Economics , 18(2), 227–254.

16.

Driver

, Grosman

, & Scaramozzino

(2020). Dividend policy and investor pressure. Economic Modelling , 89, 559–576.

17.

Erhan

& Ozgur

(2017). Institutional investment horizon and dividend policy: An empirical study of UK firms. Financial Letters , 24(1), 291–300.

18.

Fairchild

, Gunney

, & Thamatawee

(2013). Corporate dividend policy in Thailand: Theory and evidence. International Review of Financial Analysis , 3(10), 129–151.

19.

Gaver

J. J.

, & Gaver

K. M.

(1993). Additional evidence on the association between investment opportunity set and corporate financing, dividend and compensation policies. Journal of Accounting and Economics , 16, 125–140.

20.

Gordon

M. J.

(1963). Optimal investment and financing policy. Journal of Finance , 1(1), 264–272.

21.

Gujarati

D. N.

, & Porter

D. C.

(2009). Basic econometrics (5th Ed.). Mc Graw Hill Inc.

22.

Harakeh

(2020). Dividend policy and corporate investment under information shocks. Journal of International Financial Markets, Institutions, and Money , 65. https://doi.org/10.1016/j.intfin.2020.101184

23.

Holtemöller

(2002). Identifying a credit channel of monetary policy transmission and empirical evidence for Germany. Paper Presented at the Freie Universität, Berlin. http://amor.rx.hu-berlin.de/h32330ay

24.

Ijeoma

N. B.

(2017). The effect of global financial crisis on the performance of Nigerian Stock Exchange. International Journal of Accounting and Economic Studies , 1, 46–50.

25.

K. L.

, Pesaran

M. H.

, & Shin

(2003). Testing for unit root in heterogeneous panels. Journal of Econometrics , 115(1), 53–74.

26.

Jones

, & Sharma

(2001). “The impact of free cash flow, financial leverage and accounting regulation on earnings management in Australia’s “old” and “new” economies”. Managerial Finance , 27(12), 18–39.

27.

Kajola

S. O.

, Desu

A. A.

, & Agbanike

T. F.

(2015). Factors influencing dividend payout policy decisions of Nigeria listed firms. International Journal of Economics, Commerce and Management , 3(6), 539–557.

28.

Kallapur

, & Trombley

M. A.

(2001). The investment opportunity set, determinants, consequences and measurement. Managerial Finance , 27(3), 3–15.

29.

Kim

, & Nelson

(1999). Has the US economy become more stable? A Bayesian Approach based on a Markov-Swithching model of the Business Cycle. The Review of Economics and Statistics , 81(4), 608–616.

30.

Lease

R. C.

, John

, Kalay

A. L.

Loewenstern Savig

O. D.

(2000). Dividend policy: Its impact on firms’ vale . Harvard Business School Press.

31.

Leahy

, & Whited

(1996). Effect of uncertainty on investment: Some stylized facts. Journal of Money, Credit and Banking , 28(2), 64–83.

32.

Levine

, Lin

, & Chu

C. J.

(2002). Unit root test in panel data: Asymptotic and finite-sample properties. Journal of Econometrics , 108(1), 1–24.

33.

Litner

(1962). Dividends, earnings, average stock prices, and supply of capital to corporations. The Review of Economics and Statistics , 64, 253–269.

34.

Litzenberger

R. H.

, & Ramaswany

(1979). The effect of personnel taxes and dividends on capital assets prices: Theory and empirical evidence. Journal of Finance and Economics , 7(2), 163–195.

35.

Megginson

W. L.

, Smart

S. B.

, & Gitman

L. J.

(2007). Corporate finance . Thomson/South-Western.

36.

Miller

M. H.

, & Modigliani

(1961). Dividend policy growth and the valuation of shares. Journal of Business , 34, 411–433.

37.

Miller

M. H.

, & Rock

(1985). Dividend policy under asymmetric information. Journal of Finance , 40(4), 1031–1051.

38.

Modigliani

, & Miller

M. H.

(1958). The cost of capital, corporate finance, and the theory of investment. The American Economic Review , 48(3), 261–297.

39.

Myers

S. C.

(1977). Determinant of corporate borrowing. Journal of Financial Economics , 5, 147–175.

40.

Parveen

, Satti

Z. W.

, Subhan

Q. A.

, & Jamil

(2020). Exploring market overreaction, investors’ sentiments and investment decisions in an emerging stock market. Borsa Istanbul Review , 20(3), 224–235.

41.

Proshere News. (2017). A dividend payment in the Nigerian capital market: A view . Proshere News. https://www.proshareng.com/news/Investors%20NewsBeat/Dividend-Payments-in-the-Nigerian-Capital-Market—A-View/16841

42.

Sims

C. A.

(1980). Macroeconomics and reality. Econometrica , 48(1), 1–48.

43.

Smith

, & Watts

(1992). The investment opportunity set and corporate financing, dividend and compensation policies. Journal of Financial Economics , 32, 263–292.

44.

Sofer

, Schnell

, & Drori

(1996). Industrial zones and Arab industrialization in Israel. Human Organisation , 55(4), 465–474.

45.

Subramanian

, Toney

J. H.

, & Jayachandran

(2011). The evolution of research and development in the pharmaceutical industry: Toward the open innovation model – can pharma reinvent itself? International Journal of Business Innovation and Research , 5(1), 63–74.

46.

Tekin

, & Polat

A. Y.

(2021). Do market differences matter on dividend policy? Borsa Istanbul Review , 21(2), 197–208.

47.

Tsai

, & Wu

(2015). Bond and stock market response to unexpected dividend changes. Journal of Empirical Finance , 30, 1–15.

48.

Woolrige

, & Gosh

J. C.

(1988). An analysis of shareholder reaction to dividend cuts and omissions. Journal of Financial Research , 11(4), 281–294.

49.

Yao

, Zhang

, & Hu

(2020). Does having a semi-mandatory dividend policy enhance investor confidence? Research on dividend-financing behavior. Economic Systems, 4 . https://doi.org/10.1016/j.ecosys.2020.100812

50.

Yarba

, & Yassa

A. D.

(2021). Does stock market listing boost or impede corporate investment? (Working Papers 2112). Research and Monetary Policy Department, Central Bank of the Republic of Turkey.

51.

Yeo

(2018). Role of free cash flows in making investment and dividend decision: The case of the shipping industry. The Asian Journal of Shipping and Logistics , 34(2), 114–118.

Dynamic Interactions in the Nexus Among Dividend,Firms’ Investment Behaviour and Value of Selected Quoted Companies in Nigeria (2001–2019)

Abstract

Keywords

Introduction

Literature Review

Theoretical Issues

Empirical Issues

Data Description

Descriptive Statistics of Data Series for the Dynamic Relationship Among Dividend Policy, Firms’ Investment Behaviour and Value of Quoted Companies.

Correlation Matrix of Data Series for the Dynamic Relationships among Dividend Policy, Firms’ Investment Behaviour and Value of Quoted Companies.

Research Methods

Model of Dynamic Relationship among Dividend Pay-out Policy, Firms’ Investment Behaviour and Value

Empirical Analysis

Results

Unit Root Test for the Dynamic Relationships among Dividend Pay-out Policy, Firms’ Investment Behaviour and Value of the Sampled Companies.

Estimation of Dynamic Relationship Among Dividend Pay-out Policy, Firms’ Investment Behaviour and Value of Quoted Firms in Nigeria

Matrix B.

Optimal Lag Selection.

Structural Vector Autoregression Estimates

Short-run Pattern Matrix B.

Estimated Parameters for Matrix B.

Estimated Matrix B.

Discussion of Findings

Impulse Response Analysis

Conclusion and Policy Recommendations

Footnotes

Declaration of Conflicting Interests

Funding

ORCID iD

References