Board meetings and bank performance in Africa

Abstract

This study examines the relationship between a board meeting and banks performance in Africa. This paper provides insight on this question after taking into account the endogeneity of the relationship between board meetings and performance. Specifically, we use the GMM technique and a sample of 635 banks from 48 countries in Africa between 2000 to 2016 to test our hypothesis and found that more board meetings, averagely 6, reduce banks’ performance in sub-Sahara Africa. In the Northern Africa context, with an average board meeting of 7.68, however, we document a positive and significant association between a board meeting and bank performance. Our result suggests that fewer board meeting enhances the shareholder value of Banks in Sub-Sahara Africa but not their counterparts in North Africa. Our paper provides insights to policymakers responsible for improving the governance mechanisms in African banks.

Keywords:

• Corporate governance
• board of directors
• board process
• board monitoring
• African banks

JEL Classifications:

• G21
• G34
• G38

PUBLIC INTEREST STATEMENT

Are Board meetings beneficial to shareholders of banks in Africa? Our evidence from 48 out of the 54 countries in Africa suggest that board meeting enhances bank profitability in Southern, Eastern, and North Africa. Board meetings, however, diminish bank profitability in Western Africa. The practical implication is that more board meeting is beneficial to shareholders in Southern, Eastern, and North Africa but not Western Africa. Our policy contributions are threefold. First, regulators as well as both bank boards and shareholders in Southern, Eastern, and North Africa are advised to promulgate reforms and policies aimed at encouraging more board meetings, at most 6, 6, and 8 per annum, respectively. Second, their colleagues in Western Africa, however, must advocate for reforms and policies aimed at fewer (not more than 6) board meetings. • Finally, a one size fits all board meetings agenda should not be encouraged in the African Context, practitioners and reformers are warned.

1. Introduction

What is the relationship between a board meeting and banks’ performance? Twenty-two years after the seminal work of Vafeas (1999), highlighting a negative relationship between board-meeting frequency and firm performance, the answer to this question remains both complex and unclear. One view is that board meetings are beneficial to shareholders (Lipton & Lorsch, 1992; Conger et al., 1998; Xie et al., 2003; Allegrini & Greco, 2013; González & García-Meca, 2014; Nguyen et al., 2021), suggesting that directors in boards that meet more frequently are more likely to perform their duties in accordance with shareholders’ interests. Prior research, for example, finds board and audit committee meeting frequency reduced levels of discretionary current accruals (González & García-Meca, 2014; Xie et al., 2003) but enhanced firms’ transparency (Allegrini & Greco, 2013), as well as both environmental (Nguyen et al., 2021) and financial (Abdul Gafoor et al., 2018; M.W. Saleh et al., 2021) performance.

In contrast, busy directors (Fich & Shivdasani, 2012) and directors’ external job demands meetings (Carpenter & Westphal, 2001) limit the director’s ability to do his/her homework. The entire board also devotes only 48% of total director meetings time to their monitoring role while powerful CEOs do not only dominate board meetings and procedures but also set the agenda (Jensen, 1993). Altogether, these render the board meetings ineffective, with negative implications on performance. More board meeting is related to prior performance (Vafeas, 1999), firm and governance characteristics (Brick & Chidambaran, 2010), corporate fraud (Khanna et al., 2015), implying board meetings serve as a fire-fighting device but not a proactive value enhancing strategy.

There is a related strand of the literature that considers board meetings as important determinants of performance in Africa (see Kyereboah-Coleman, 2008; Eluyela et al., 2018; Ntim & Osei, 2011). Ntim and Osei (2011), in particular, provide support for the recommendations of King II, highlighting that boards should at least meet four times annually. They however questioned the “one-size fits all, due in part to the non-linear relationship between corporate board meetings and corporate performance. These studies, however, are limited in several respects. For example, data used in Kyereboah-Coleman (2008), Ntim and Osei (2011) dates back to 2001 and 2007, respectively. Eluyela et al.’s (2018) study focused on listed sampled deposit money banks in Nigeria. Overall, there is no comprehensive study on the value of board meetings in the Africa context, an environment where enforcement of regulations is weak. This gap, in turn, implies generalization of findings of prior studies in the Africa context may be problematic. This study attempts to find this gap by using the GMM technique, a sample of 635 banks from 48 Africa countries between 2000 to 2016 to examine whether active boards, measured by the frequency of board meetings, are effective in discharging their board monitoring role, thereby enhancing corporate performance in Africa. In sum, this paper examines whether board meeting is related to banks” performance in Africa.

Critics, may ask, why Africa? Various codes of corporate governance require corporate boards to hold formal meetings to discharge the oversight duties. King III code of governance, for instance, prescribes at least four meetings annually for corporate boards in South Africa. Elsewhere in Nigeria and Egypt, voluntary corporate governance codes demand at least a board meeting every three months. The spirit underlying these reforms is to advance active board with implications performance. Empirical evidence in the Africa context saves Eluyela et al. (2018), however, has disappeared after Ntim and Osei (2011). Accordingly, both the academic and practitioners press are calling for more research on board meeting and performance nexus in the context of cross country (Agyei-Mensah, 2021; Eluyela et al., 2018). This study offers the opportunity to examine board reforms imported from developed countries into the context of Africa by examining the impact of board meetings on banks’ performance in Africa. The banking sector is chosen due to its impact on socio-economic development in Africa including job creation and attraction of both internal and external investors.

We provide insight on the board meeting and bank performance nexus from 48 countries in Africa. Put differently, the first cross-country study to enrich our understanding of the efficacy of a corporate board meeting is the subject of reforms but overlooked in the vast literature of corporate governance in the Africa context. Finally, we document that firms in Sub-Sahara, Southern, and Eastern Africa Regions may benefit from fewer board meetings, say less than 6, but not their counterparts from the Northern Africa context, implying reforms aiming at a “one size fit all” number of board meeting approach in the Africa context should not be encouraged.

The rest of the paper is structured as follows. Section 2 discusses the literature review. Section 3 contains the method. Section 4 deals with empirical analyses. Section 5 concludes.

2. Literature review

2.1. Agency theory

2.1.1. Theory and hypotheses

Agency theory prescribes board monitoring as one of the means to control the notorious conflict of interest between CEO and shareholders (Fama & Jensen, 1983), emphasizing that enhanced board monitoring through the board and sub-committee meetings reduce the moral hazard and information asymmetric problems predominant in the modern-day corporation Kanagaretnam et al., 2007), thereby reducing opportunistic behavior by the CEO, with favorable implications on the interest of the shareholders (Jensen & Meckling, 1976; Méndez & Garcia, 2007). Thus, frequent board meetings offer the avenue for outside directors to perform their monitoring duties by introducing an independent voice on firms’ strategic plan, the integrity of financial statements, risk strategy, and evaluation of the CEO’s agenda and performance (Appiah & Amon, 2017; Vafeas, 1999). Here, frequent board meeting shows active monitoring by board members which ensures that the right strategic decisions are taken and implemented by the management of firms (Agyei-Mensah, 2021; Burke et al., 2019; Conger et al., 1998; Grove et al., 2011; Jensen, 1993; Jensen & Meckling, 1976; Vafeas, 1999) with a positive impact on firm performance (M.W. Saleh et al., 2021; Mangena & Tauringana, 2008; Musleh Alsartawi, 2019; Ntim et al., 2017; Vafeas, 2003).

2.1.2. Board meetings and bank performance

Empirically, little is known about the association between board meetings and bank performance. Much attention on the aforementioned subject employed datasets from developed and emerging economies in Asia, Europe, and America. Liang et al. (2013), for example, examine board characteristics and performance of bank asset quality using a sample of 50 largest Chinese banks from 2003 to 2010. They find that the number of board meetings has a positive impact on the bank performance (ROA). Similarly, in Australian banks, Salim et al. (2016) find a positive effect of frequency of board meetings on bank performance. Consistent with agency theory, Grove et al. (2011) used a dataset of US commercial banks to examine the corporate governance and performance in the wake up of the financial crisis. They employed a multiple regression model with a sample of 236 public commercial banks in the US. Their findings reveal that the frequency of board meetings is positively associated with financial performance. The results indicate that boards of US public commercial banks that meet more frequently increase the bank’s financial performance. Recent evidence documents that board meeting is positively related to return on assets (Abdul Gafoor et al., 2018) and return on equity (Mohamed et al., 2016).

However, Lipton and Lorsch (1992) argue that various routine tasks including the presentation of management reports and other formalities take much of the meeting and reduce the time that should be available for directors to monitor management effectively. Similarly, Vafeas (2009) and Vafeas (1999), and Musleh Alsartawi (2019) add that refreshment, travel expenses, and meeting fees which are associated with the meetings increase agency cost. These, in turn, could adversely affect firm performance. Recent scholars find that board meeting is negatively related to investment decisions (Agyei-Mensah, 2021) and firm performance (Rodriguez-Fernandez et al., 2014).

These contrasting views notwithstanding, literature seems to converge on the notion that independent outside directors serving on firm boards are likely to insist on more board and committee meetings to enhance their ability to monitor the financial growth, profitability, and survival Appiah & Amon, 2017). Therefore, corporate boards that meet less frequently are less likely to be effective in discharging their oversight duties (Conger et al., 1998; Jensen, 1993; Lipton & Lorsch, 1992). This said, in line with agency theory, adequate monitoring by the board of directors is required to ensure that the management takes the interest of the owners into account when making decisions. If the management of African banks is to do their work well and act in the best interest of the owners or shareholders, the performance of African banks can improve significantly. We align with the agency theoretical lens and in the context of the board meetings and performance in Africa Banks, we state our hypothesis as follows:

H1: there is a significant positive association between the frequency of banks board meetings and banks performance in Africa

H1a: there is a significant positive association between the frequency of banks board meetings and banks Return on Assets in Africa

H1b: there is a significant positive association between the frequency of banks board meetings and banks Return on Equity in Africa

3. Methodology

3.1. Data source

We extract data on bank-specific variables from Orbis Bank Focus and BankScope databases. The data on the internal corporate governance variable, board meeting, were also obtained from the annual reports available at the banks’ websites. However, there is corporate governance information of a few banks that were obtained from the BoardEx database. Finally, data on Gross Domestic Product and Corruption were obtained from the World Bank Group websites.

3.2. Sample selection criteria

All banks included in our sample had at least five years of information between 2005 − 2016. 2005 was chosen due to the availability of data. Another reason is to capture information before, during, and after the 2007/2008 financial crises. Our unique sample included listed unlisted, small, medium, and large banks. These allow our sample to be bigger, give a broader picture from the findings of the present study, and enhance the generalisability of the results. During data collection, 1502 African banks were found on the BankScope database which was exported. Some banks were repeated twice or three times and for that matter, only one was selected; others had less than five years’ information and were also removed.

Our final sample consists of 635 with 10795 bank years’ information from 48 countries out of the 54 countries in Africa (see, Table 1). Data was not available for the omitted 6 countries. In all, our 635 banks operate in at least one of the 17 specializations, with commercial (62.8%) and investment (8%) banks dominating (see, Table 2).

Table 1. Number of banks selected from each country

No.	Country	No. of Banks	No.	Country	No. of Banks
1	Algeria	17	25	Madagascar	5
2	Angola	17	26	Malawi	12
3	Benin	5	27	Mali	8
4	Botswana	16	28	Mauritania	7
5	Burkina Faso	7	29	Mauritius	16
6	Burundi	5	30	Morocco	18
7	Cameroon	9	31	Mozambique	16
8	Cape Verde	6	32	Namibia	10
9	Central African Republic	2	33	Niger	4
10	Chad	3	34	Nigeria	28
11	Cote D’Ivoire	12	35	Rwanda	9
12	Djibouti	5	36	Senegal	11
13	DR. Congo	12	37	Seychelles	6
14	Egypt	26	38	Sierra Leone	7
15	Ethiopia	15	39	South Africa	57
16	Gabon	7	40	South Sudan	2
17	Gambia	2	41	Sudan	19
18	Ghana	29	42	Swaziland	7
19	Guinea	3	43	Tanzania	29
20	Guinea Bissau	1	44	Togo	10
21	Kenya	43	45	Tunisia	31
22	Lesotho	4	46	Uganda	24
23	Liberia	2	47	Zambia	22
24	Libya	9	48	Zimbabwe	20
	Total number of Banks				635

Table 2. Specialisation of the banks selected for the study

No.	Bank specialisation	No. of banks	Percentage
1	Bank holdings company	33	5.2%
2	Central bank	26	4.1%
3	Clearing and custody institution	1	0.2%
4	Commercial bank	399	62.8%
5	Corporative bank	2	0.3%
6	Credit institution	27	4.3%
7	Finance company	27	4.3%
8	Investment and trust corporation	2	0.3%
9	Investment bank	51	8.0%
10	Islamic bank	24	3.8%
11	Micro-finance institution	18	2.8%
12	Multi-lateral governmental bank	6	0.9%
13	Other non-banking credit institution	1	0.2%
14	Private banking/Asset mgt. comp	1	0.2%
15	Real estate and mortgage bank	8	1.3%
16	Savings bank	6	0.9%
17	Securities firm	3	0.5%

3.3. Model specification

Following Nguyen et al. (2021), we employ GMM as our main estimator. GMM was used due to its advantages over other techniques, such as resolving the problems of autocorrelation endogeneity, profit persistence, and unobserved heterogeneity. To achieve this, the following regression equation is formulated to test empirically our hypothesis, H1:

(1) $\begin{array}{rl}& RO{A}_{it}={\beta }_0+{\beta }_{1}SIZ{E}_{it}+{\beta }_{2}EQT{A}_{it}+{\beta }_{3}NLT{A}_{it}+{\beta }_{4}COS{T}_{it}+{\beta }_{5}CO{R}_{it}+{\beta }_{6}GD{P}_{it}+\\ & {\beta }_{7}MEETING{S}_{it}+\delta 0_{\hspace{0.17em}}+{\epsilon }_{it}\end{array}$(1)

(2) $\begin{array}{rl}& RO{E}_{it}={\beta }_0+{\beta }_{1}SIZ{E}_{it}+{\beta }_{2}EQT{A}_{it}+{\beta }_{3}NLT{A}_{it}+{\beta }_{4}COS{T}_{it}+{\beta }_{5}CO{R}_{it}+{\beta }_{6}GD{P}_{it}+\\ & {\beta }_{7}MEETING{S}_{it}+\delta 0_{\hspace{0.17em}}+{\epsilon }_{it}\end{array}$(2)

where β₁ to _β7 represent the coefficient of each variable. β₀ is the intercept., ε_it is the error term. Table 3 display a summary of the measurement of our variables. Our dependent variable is financial performance, proxied by return on assets (ROA_it is the performance of bank i at time t) and return on equity (ROE_it is performance of bank i at time t). These accounting performance indicators are well established in the literature (e.g., Gafoor et al., 2018; Ntim & Osei, 2011). The independent corporate governance variable is board meeting (MEETINGS_it), which is the number of board meetings of bank i at time t. This is also in line with prior studies including Vafeas (1999), Coleman (2008), Ntim and Osei (2011), Appiah et al. (2017), Gafoor et al. (2018), Vitolla et al. (2020).

Table 3. Summaries of measures and variables

Variable	Measurement	Expected sign
Panel A: Performance Variables
ROA	Net income/total assets (%)
ROE	Net income/shareholder’s equity (%)
Panel B: Corporate governance variables
MEETINGS	The number of times that the board meets per year	+
Panel C: Control Variables
LNTA	Natural log of total assets	+
COST	Overheads/net interest revenue plus other operating income (%)	-
EQTA	Equity divided by total assets (%)	+
NLTA	Net loans divided by total assets (%)	-
LNGDP	Annual GDP growth rate	+
COR	Rank of corruption perception from World bank (corruption perception index)	-
CRISIS	Dummy variable for 2007/2008 financial crisis	-

We control several firm-specific and macroeconomic indicators. First, these variables are positively related to banks’ performance. These are firm size (SIZE_it), measured by the size of bank i at time t (see Kyereboah-Coleman, 2008; Gafoor et al., 2018), equity to total assets (EQTA_it) of bank i at time t (Ramlan & Adnan, 2016), and Gross Domestic Product (GDP_it) of country i at time t (Adelopo et al., 2018). Second, Adelopo et al.’s (2018) study displays a positive association between bank-specific factors and bank performance before, during, and after the financial crisis. This also underlines the inclusion of financial crisis. δ₀ is a dummy for the crisis period, 1represents 2007/2008 and 0 otherwise. Finally, Net loan to total asset (NLTA_it) of bank i at time t, and corruption (COR_it) of country i at time t, cost to income ratio (COST_it) of bank i at time t, however, are positively related respectively to Bank loan loss provisions (see, Ozili, 2019), risk-taking behavior of banks (Chen et al., 2015.) and bank efficiency (see the detailed argument in Hess & Francis, 2004), implying negative association with banks performance.

4. Empirical analyses and discussion

4.1. Descriptive statistics

Panel A of Table 4 presents the measure of bank performance, ROA, and ROE. ROA (ROE) ranges from −6.91% (−49.36) and 9.30% (60.33%), with an average of 1.78% (13.96%) and standard deviation of 2.74% (19.54%). Panel B of Table 4 presents the independent corporate governance variable, board meeting. The board meeting has minimum and maximum numbers of 0 and 38 respectively and a standard deviation of 4.20. The average number of board meetings held by the banks is 6.26 per year. Panel C of Table 4 presents all the control variables. Bank size has a minimum value of −1.70, a maximum value of 9.65, and a standard deviation of 1.71. The mean total asset (LNTA) of the banks is 3.55. Our results compare favorably with Gafoor et al.’s (2018) India findings of ROA(ROE) of 1.01(8.34) but not the Bank Size (Board meetings) of 13.08(11). Our results compare favorably to the bank size (10.53) and board meeting (1) reported by Eluyela et al. (2018) Nigeria study but not board meeting (10.53) reported by Kyereboah-Coleman’s (2008) cross county study of Ghana, Kenya, South Africa, and Nigeria.

Table 4. Summary descriptive statistics of all variables

Variables	Mean	Median	Std. Dev.	Min.	Max.	Skewness	Kurtosis	Observations
Panel A: Performance (dependent) variables
ROA	1.78	1.71	2.74	−6.91	9.30	−0.35	5.71	7434
ROE	13.96	14.04	19.54	−49.36	60.33	−0.65	5.33	7434
Panel B: Corp. governance variables
MEETINGS	6.26	5.0	4.20	0.00	38.00	3.59	20.94	1447
Panel C: Control Variables
LNTA	3.55	3.17	1.71	−1.70	9.65	0.28	2.92	7510
COST	62.70	59.00	28.37	14.46	159.21	1.23	5.41	6810
EQTA	16.34	11.77	14.51	2.70	72.91	2.45	9.10	7493
NLTA	47.59	48.84	21.39	2.77	90.01	−0.16	2.50	7238
LNGDP	6.74	7.32	2.46	−0.81	11.15	−0.24	2.16	10768
COR	35.40	32.70	22.23	0.48	85.85	0.25	1.87	10137
δ	0.12	0.00	0.32	0.00	1.00	2.37	6.63	10790

Note: This table presents the following variables: performance measured by return on assets (ROA), performance measured by return on equity (ROE), bank size (SIZE), equity to assets (EQTA), net loans to assets (NLTA), cost-to-income-ratio (COST), corruption (COR), gross domestic product (GDP), number of board meetings (MEETINGS), δ is dummy for the crisis period.

The cost-to-income ratio has a minimum value of 14.46, a maximum value of 159.21, a standard deviation of 28.37 with a mean of 62.70%. A bank with a lower cost-to-income ratio represents a higher efficiency of the bank and vice-versa. The equity to assets ratio has a minimum, maximum, standard deviation, and mean values of 2.70%, 72.91%, 14.5, and 16.34% respectively. Net loans to total assets range from a minimum of 2.77% to a maximum of 90.01%. Net loans to total assets have a mean value of 47.59% and a standard deviation of 21.39%. A bank with a very high ratio of net loans to total assets may not be able to meet its liquidity requirements in the event of unforeseen circumstances. The minimum and maximum values of GDP recorded from the banks under study are −0.81 and 11.15 respectively. The average GDP is 6.74 and has a standard deviation of 2.46. A high corruption figure means low corruption and a lower figure means high corruption. 0.48, 85.85, 22.23, and 35.40 represent minimum, maximum, standard deviation, and mean corruption values respectively.

Table 5 displays the Pearson and Spearman correlation matrix. The co-efficient are all below 0.7 save the those recorded by the two proxies for the dependent variables; implying the absence of multicollinearity for our independent variables.

Table 5. Pearson (left) and Spearman (right) correlation matrices of the variables

Variables	1	2	3	4	5	6	7	8	9	10
ROA	1	.765**	−.071**	.319**	−.024*	−.005	.017	−.551**	.059**	−.058*
ROE	.732**	1	.075**	−.182**	−.079**	.018	.000	−.493**	.072**	−.057*
3. LNTA	−.055**	.033**	1	−.250**	.047**	.266**	−.036**	.004	−.050**	.082**
4. EQTA	.206**	−.135**	−.184**	1	.070**	−.027*	−.004	−.090**	−.024*	−.011
5. NLTA	−.007	−.051**	.035**	−.017	1	−.019	.236**	−.054**	−.012	−.052
6. LNGDP	−.012	−.009	.224**	−.053**	−.017	1	−.298**	.115**	.002	.127**
7. COR	.067**	.025*	−.051**	.117**	.232**	−.304**	1	−.105**	.018	.028
8. COST	−.581**	−.560**	.012	−.027*	−.093**	.090**	−.101**	1	−.025*	−.004
9. δ	.039**	.053**	−.054**	.003	−.012	.000	.014	−.019	1	.029
10.MEETINGS	−.068*	.034	.041	−.031	−.096**	.029	−.084**	.037	.011	1

Note: ***, **, * indicate significance at 1, 5 and 10% respectively. Robust standard errors in parenthesis. This table presents the following variables: performance measured by return on assets (ROA), performance measured by return on equity (ROE), bank size (SIZE), equity to assets (EQTA), net loans to assets (NLTA), cost-to-income-ratio (COST), corruption (COR), gross domestic product (GDP), number of board meetings (MEETINGS).

4.2. Results of board meeting and performance

Table 6 presents the empirical findings of the relationship between board meetings and bank performance using the GMM regression technique. The result shows that Board meetings have an insignificant negative impact (β = −0.0724, p > 0.05) on ROA but have a significant negative impact (β = −0.760, p < 0.05) on ROE. These results reject H1a and H1b, which postulated a statistically significant positive relationship between board meetings and bank performance, measured by return on assets and equity in Africa, respectively. The negative impact on ROE implies that the agency cost (for example, refreshments, travel expenses, directors’ meetings, and time) associated with holding more board meetings in Africa outweighs the benefit, implying the frequent board meetings though perceived as a good corporate governance practice, corporate board in Africa may not always devote quality time to discuss critical issues relating to the performance. As a result, such meetings bring costs, which will negatively affect bank performance. Therefore, a smaller number of board meetings is better for Banks in Africa to improve performance. Our finding is in line with Lipton and Lorsch (1992) who argue that meeting routine tasks such as reading and adoption of previous minutes and presentation of management reports consume much of the meetings, and this minimizes the amount of time that is supposed to be available to outside directors to effectively monitor corporate performance. In contrast, our findings do not support the agency theory notion (Jensen & Meckling, 1976), suggesting that frequent board meetings could increase bank performance. Our finding is at variance with the results of previous empirical findings (e.g., Gafoor et al., 2018; Grove et al., 2011; Liang et al., 2013; Salim et al., 2016), highlighting a positive association between board meetings and bank performance.

Table 6. GMM regressions results of board meetings and bank performance

Model	(1)	(2)
VARIABLES	Overall	Overall
L.ROA	0.0884*
	(0.0475)
L.ROE		0.134***
		(0.0493)
MEETINGS	−0.0724	−0.760**
	(0.0452)	(0.311)
Size	−0.137*	−0.552
	(0.0764)	(0.445)
EQTA	−0.00645	0.0712
	(0.0245)	(0.243)
NLTA	−0.0357***	−0.0217
	(0.0116)	(0.0922)
COST	−0.0469***	−0.235***
	(0.00843)	(0.0624)
COR	−0.00892	0.0930
	(0.0105)	(0.0999)
LNGDP	−0.0157	−0.771
	(0.111)	(0.865)
δ	0.411***	4.027***
	(0.107)	(0.653)
Constant	7.961***	34.49**
	(1.561)	(13.70)
Observations	1,050	1,050

Notes: This table is based on generalised method of moments (GMM) panel data estimator. ***, **, * indicate significance at 1, 5 and 10% respectively. Robust standard errors in parenthesis. This table presents the following variables: performance measured by return on assets (ROA) and return on equity (ROE) in models 1 and 2, respectively, lag of ROA (L.ROA), bank size (SIZE), equity to assets (EQTA), net loans to assets (NLTA), cost-to-income-ratio (COST), corruption (COR), natural logarithm of gross domestic product (LNGDP), number of board meetings (MEETINGS), δ is dummy for the financial crisis period.

4.3. Regional analyses

We first divided our sample between Sub-Saharan Africa and North Africa.¹ Table 7 contains the GMM results. There is a significant negative association between board meetings and bank performance, measured by both ROA (β = −0.0949, p < 0.05) and ROE (β = –0.484, p < 0.05), based on Sub-Sahara Africa, with average board meetings of 6. However, the association between board meetings and bank performance is significant and positive, measured by both ROA (β = 0.0567, p < 0.01) and ROE (β = 0.846, p < 0.01), based on North Africa, with average board meetings of 8. The results indicate that while a smaller number of board meetings increases bank performance in Sub-Sahara Africa significantly, more board meetings are required to increase bank performance in North Africa. The difference in the results between the two regions may probably be due to differences in board structure and composition among the two regions. The positive association between board meetings and bank performance is in line with the agency theory (Jensen & Meckling, 1976). However, the negative association between board meetings and bank performance is consistent with some previous empirical findings (e.g., Abdul Gafoor et al., 2018; Grove et al., 2011; Liang et al., 2013; Salim et al., 2016).

Table 7. GMM regressions results of board meetings and bank performance

Model	(1)	(2)	(1)	(2)	(1)	(2)	(1)	(2)	(1)	(2)
VARIABLES	Sub-Sahara	Sub-Sahara	North	North	South	South	East	East	West	West
L.ROA	0.0801**		0.301***		0.171***		0.0405**		−0.251***
	(0.0393)		(0.0137)		(0.0155)		(0.0168)		(0.0573)
L.ROE		0.229***		0.323***		0.0382**		0.0670**		0.257***
		(0.0453)		(0.0279)		(0.0173)		(0.0311)		(0.0560)
MEETINGS	−0.0949**	−0.484**	0.0567***	0.846***	−0.115***	−0.658**	−0.127***	−0.958***	−0.0247	−1.112***
	(0.0446)	(0.226)	(0.00360)	(0.0189)	(0.0330)	(0.251)	(0.0260)	(0.174)	(0.0184)	(0.355)
Size	−0.178**	−0.838	−0.0726***	−0.314***	−0.123**	0.217	0.0302	0.614	−0.640***	−3.112***
	(0.0885)	(0.508)	(0.0136)	(0.0838)	(0.0501)	(0.295)	(0.0713)	(0.373)	(0.112)	(0.663)
EQTA	−0.0277	−0.0849	0.0326***	−0.204***	0.0291***	−0.242***	−0.0637***	−0.511***	0.0524**	−0.156
	(0.0230)	(0.209)	(0.00325)	(0.0301)	(0.00640)	(0.0648)	(0.0124)	(0.107)	(0.0211)	(0.182)
NLTA	−0.0274**	0.0360	−0.0108***	−0.139***	−0.00271	−0.230***	−0.0829***	−0.110**	−0.0386***	0.0364
	(0.0107)	(0.0776)	(0.00173)	(0.0176)	(0.00333)	(0.0330)	(0.00373)	(0.0491)	(0.00742)	(0.161)
COST	−0.0518***	−0.182***	−0.0568***	−0.469***	−0.0445***	−0.389***	−0.0602***	−0.306***	−0.0700***	−0.564***
	(0.00785)	(0.0567)	(0.00160)	(0.0181)	(0.00163)	(0.0200)	(0.00530)	(0.0279)	(0.00877)	(0.0481)
COR	−0.00957	0.0579	0.00481**	0.0590***	0.0106**	−0.0752**	−0.0497***	−0.0382	−0.0220	−0.975***
	(0.00960)	(0.0820)	(0.00213)	(0.0212)	(0.00457)	(0.0305)	(0.00656)	(0.0735)	(0.0227)	(0.137)
LNGDP	−0.0506	−0.311	−0.163***	−1.571***	−0.0428	1.796***	−0.0284	−0.300	−0.439***	−6.370***
	(0.100)	(0.695)	(0.0221)	(0.151)	(0.0348)	(0.587)	(0.0654)	(0.450)	(0.129)	(0.932)
δ	0.374**	4.481***	0.673***	5.032***	0.803***	3.413***	0.691***	5.978***	0.152	7.436***
	(0.148)	(0.814)	(0.0477)	(0.280)	(0.0457)	(0.608)	(0.0433)	(0.418)	(0.113)	(0.879)
Constant	8.989***	27.78**	4.770***	45.46***	4.919***	52.12***	13.25***	52.67***	13.81***	138.8***
	(1.553)	(12.52)	(0.172)	(1.867)	(0.483)	(3.408)	(0.666)	(5.871)	(1.472)	(18.08)
Observations	893	893	157	157	372	372	484	484	143	143

Notes: This table is based on generalised method of moments (GMM) panel data estimator. ***, **, * indicate significance at 1, 5 and 10% respectively. Robust standard errors in parenthesis. This table presents the following variables: performance measured by return on assets (ROA) and return on equity (ROE) in models 1 and 2, respectively, lag of ROA (L.ROA), bank size (SIZE), equity to assets (EQTA), net loans to assets (NLTA), cost-to-income-ratio (COST), corruption (COR), natural logarithm of gross domestic product (LNGDP), number of board meetings (MEETINGS), δ is dummy for the financial crisis period.

We further sub-divided Sub-Sahara Africa into three sub-regions namely, Southern, Eastern, and Western Africa to see if there are any differences in the results. These sub-samples record average board meetings of 5.52, 6,46, and 5.75, respectively. Central Africa was excluded because there was not enough data available. The relationship between board meetings and bank performance in Southern (β = −0.115, p < 0.01) and Eastern Africa (β = −0.127, p < 0.01) is significant and negative, based on both accounting measures, ROA and ROE, indicating that fewer meetings are required to improve bank performance in Southern and Eastern Africa. The relationship between board meetings and bank performance in Western Africa is negative and significant (β = −1.112, p < 0.01) based on ROE. This indicates that Western Africa also benefits from a smaller number of board meetings to improve bank performance.

4.4. Robustness test

We use OLS, Fixed effect, and 2SLS to check the robustness of our results (see, Table 8). Overall, the results of the additional analysis (OLS, fixed effect, and 2SLS) are quantitatively and quantitatively similar to GMM’s results. Our OLS and Fixed Effects models report an R-squared of 38%-42%, implying our models are not only robust but explain at least 38% of the variation in the performance of Banks in Africa.

Table 8. Relationship between board meetings and bank performance using ROA for the overall sample

MODEL	(1)	(2)	(1)	(2)	(1)	(2)	(1)	(2)
VARIABLES	OLS	OLS	Fixed effect	Fixed effect	2SLS	2SLS	GMM	GMM
L.ROA							0.0884*
							(0.0475)
L.ROE								0.134***
								(0.0493)
MEETINGS	−0.0219	0.0495	−0.0236	−0.0355	−0.0251	−0.0248	−0.0724	−0.760**
	(0.0176)	(0.123)	(0.0246)	(0.173)	(0.0194)	(0.135)	(0.0452)	(0.311)
SIZE	−0.154***	−0.515**	−0.121***	−0.609**	−0.154***	−0.811***	−0.137*	−0.552
	(0.0361)	(0.246)	(0.0389)	(0.274)	(0.0326)	(0.229)	(0.0764)	(0.445)
EQTA	0.0343***	−0.227***	0.0437***	0.00193	0.0351***	−0.126***	−0.00645	0.0712
	(0.00642)	(0.0266)	(0.00829)	(0.0585)	(0.00566)	(0.0390)	(0.0245)	(0.243)
NLTA	−0.00653*	−0.0465**	−0.00297	0.0214	−0.00769*	−0.0465*	−0.0357***	−0.0217
	(0.00369)	(0.0227)	(0.00556)	(0.0392)	(0.00393)	(0.0271)	(0.0116)	(0.0922)
COST	−0.0524***	−0.370***	−0.0628***	−0.452***	−0.0586***	−0.414***	−0.0469***	−0.235***
	(0.00380)	(0.0247)	(0.00270)	(0.0191)	(0.00234)	(0.0163)	(0.00843)	(0.0624)
COR	0.00181	0.0348*	0.00286	0.156**	0.00386	0.0505*	−0.00892	0.0930
	(0.00287)	(0.0196)	(0.0110)	(0.0779)	(0.00430)	(0.0291)	(0.0105)	(0.0999)
LNGDP	0.0227	−0.0538	−0.934**	−10.47***	0.0473	0.0738	−0.0157	−0.771
	(0.0246)	(0.177)	(0.389)	(2.745)	(0.0391)	(0.263)	(0.111)	(0.865)
δ	0.241	4.737***	0.217	3.030**	0.331**	4.796***	0.411***	4.027***
	(0.220)	(1.554)	(0.172)	(1.212)	(0.162)	(1.150)	(0.107)	(0.653)
Constant	5.474***	43.53***	12.21***	109.7***	5.641***	44.75***	7.961***	34.49**
	(0.410)	(2.601)	(2.713)	(19.13)	(0.453)	(3.086)	(1.561)	(13.70)
Observations	1,114	1,114	1,114	1,114	1,114	1,114	1,050	1,050
R-squared	0.406	0.381	0.417	0.424

Notes: This table is based on generalised method of moments (GMM) panel data estimator. ***, **, * indicate significance at 1, 5 and 10% respectively. Robust standard errors in parenthesis. This table presents the following variables: performance measured by return on assets (ROA) and return on equity (ROE) in models 1 and 2, respectively, lag of ROA (L.ROA), bank size (SIZE), equity to assets (EQTA), net loans to assets (NLTA), cost-to-income-ratio (COST), corruption (COR), natural logarithm of gross domestic product (LNGDP), number of board meetings (MEETINGS), δ is dummy for the financial crisis period.

5. Conclusion

This study examined the relationship between board meetings and bank performance in Africa. The previous studies on the relationship between board meetings and bank performance concentrated on the developed countries and emerging countries in Asia with few studies in Africa, which positions the need and contribution for this study. The study addresses one main hypothesis and contributes to the literature on the relationship between board meetings and bank performance. Using GMM estimation, we find that board meeting has a significant negative impact on bank performance in Africa, measured by return on equity. Our result contradicts the agency theory predictions. Thus, it implies that fewer board meetings are needed to improve bank performance in Africa. The result suggests that when considering corporate governance characteristics that affect bank performance in Africa, a board meeting is a significant negative factor.

We subdivided our sample into two, Sub-Sahara and Northern Africa to see if there is any difference between the results of the two sub-regions. The result shows that as board meetings have a significant negative impact on bank performance in Sub-Sahara Africa, it has a positive impact on bank performance in Northern Africa, based on both returns on asset and return on equity. Furthermore, we subdivided our Sub-Sahara Africa sample into three, Sothern, Eastern, Western and Southern Africa and observed if there is any difference in the results within the sub-regions. The results indicate that board meeting has a significant impact on bank performance, measured by both ROA and ROE, in both Southern and Eastern Africa. Similarly, the result has a significant negative impact on bank performance, measured by ROE, in Western Africa.

Our results have theoretical, practical, and policy implications. First, the finding that frequency of corporate board meetings is negatively associated with corporate performance, measured ROA, in Western Africa raises questions on the continual use of the agency theoretical lens to study the impact of board meetings in the said context. The practical implication is that governing boards in Western Africa are advised to meet less than 6 times a year to impact on return on assets of investors. The policy implication is that regulators must promulgate reforms aimed at encouraging fewer board meetings in the Western Africa context. Second, the finding that frequency of corporate board meetings is positively associated with corporate performance, measured by both ROA and ROE, in Southern, Eastern, and North Africa supports the agency theories assertion results provide empirical support for agency theory, which suggests that corporate boards that meet more frequently have increased capacity to effectively advise, monitor and discipline management, and thereby improving corporate financial performance. The policy implication is that regulators in Southern, Eastern, and North Africa must promulgate reforms aimed at encouraging more board meetings, at most 6, 6, and 8 per annum, respectively.

6. Limitations and directions for future research

Our analysis is based on the impact of board meetings on bank accounting-based performance measures. Non-linear relationship analysis between board meetings and performance was also overlooked. For this reason, generalization of our findings to market-based performance as well as board sub-committees meetings and performance may be problematic. Again, we used the number of the board meetings as a proxy for corporate governance but the board meeting hours and agenda including an action plan to tackle performance-related issues as well as managing business routines. Here, board efficiency and effectiveness in monitoring CEO with effect on performance or otherwise can be explored using the non-linear relationship between board and sub-committee meeting on performance as well as board and sub-committees meeting hours and agenda on market-based performance and non-financial performance indicators. These are fruitful lines for future studies; the final word is not said, more research is welcomed.

correction

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Author contributions

1. Kyei, S.M conceptualized the research idea, gathered data, and wrote the first draft of the manuscript.

2. Werner, K supervised the work and provided writing assistance.

3. Appiah, K.O revised the first draft of the manuscript and positioned it critically to accommodate adequate intellectual content pre and post submission.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors received no direct funding for this research.

Notes on contributors

Simms Mensah Kyei

Simms Mensah Kyei is a PhD holder in Banking and Finance from Manchester Metropolitan University. He is an Associate member of Chartered Bankers Institute-Scotland. Simms works as a Lecturer at Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Department of Accounting Studies Education, Kumasi-Ghana. His research interest includes corporate governance, corporate failure, financial institutions risk and risk management.

Katarzyna Werner

Katarzyna Werner is a Senior Lecturer in the Department of Accounting, Finance and Banking at Manchester Metropolitan University Business School. She holds a PhD degree in Economics from the University of Manchester, UK. Her research interests mostly lie in the area of Microeconomics, in particular Decision Theory. She is also interested in Industrial Organisations and Environmental Economics.

Kingsley Opoku Appiah

Kingsley Opoku Appiah is an Associate Professor in Accounting and Corporate Governance at the Department of Accounting and Finance, KNUST School of Business. He holds a PhD from Loughborough University-UK. He is a Fellow of the Association of Chartered Certified Accountants-UK (ACCA). His research interest includes Corporate failure, Corporate Governance, IFRS, and Green and Sustainability related issues in Accounting and Finance.

Notes

1. For brevity, the descriptive statistics of the sub-sample regional analysis is available upon request.